HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
recently , birational mappings over finite fields have been investigated in terms of integrability .	recently bi-rational mappings over finite fields have been investigated in terms of integrability .
it was subsequently shown in , either do not have global scaling solutions , or the solutions are such that all their perturbations are redundant .	it had been shown in , either do not have scaling solutions , or the solutions are such that all their perturbations are redundant .
we 1the submillimeter array is a joint project between the smithsonian astrophys ical observatory and the academia sinica institute of astronomy and astrophysics and is funded by the smithsonian institution and the academia sinica .	the 5the submillimeter array is a joint project between the smithsonian astrophysical observatory and the academia sinica institute of astronomy and astrophysics , and is funded by the smithsonian institution and the academia sinica .
in appendix c , we computed the multipole moments for black saturn and orthogonal black di-ring cases as examples .	in appendix b , we compute the multipole moments for the black ring solutions with two angular momenta .
this may be also spelled out that vacuum is a most degenerate state of a system .	hence the flavour vacuum is a pure mixing condensate .
nilpotency is the basis to prove the undecidability of most of the undecidable properties of ca .	then nilpotency is the easiest problem among all decision problems on the limit set dynamics of stable ca and of ca with a unique subshift attractor .
convolutional neural networks have achieved superior performance in many visual tasks , such as object detection and segmentation .	more recently , convolutional neural networks have achieved unprecedented performance in a wide range of image classification problems .
dependence of afuv of paired galaxies on the separations .	dependence of afuv enhancement on galaxy stellar mass for spirals in s-s pairs .
capacity achieving non-linear dirty paper coding techniques have been proposed for pre-subtracting interference prior to transmission .	a capacity achieving nonlinear dirty paper coding technique has been proposed for presubtracting interference at the source prior to transmission .
generative adversarial networks define a framework for training a generative model by posing it as a minimax game .	generative adversarial networks consist of a deep generative model which is trained through a minimax game involving a competing generator and discriminator .
deep neural networks have made significant improvements in lots of computer vision tasks such as object recognition .	deep neural networks achieve impressive results on many computer vision tasks such as image recognition .
bert is a powerful language representation model , which is based on bidirectional transformer encoder .	bert uses a transformer encoder trained on masked language modeling and next-sentence prediction tasks .
yu et al integrated three types of features to construct a spatio-temporal representation , including pairwise joint distances , spatial joint coordinates , and temporal variations of joint locations .	yu et al used three categories of skeletal features , including pairwise joint distance , spatial joint coordinate , and temporal variation of joint locations , to construct a mixed representation .
iv , we summarize the results and discuss future work .	iii we discuss the physical parameters we will use and present the results .
deep neural networks have shown remarkable success in many domains , such as computer vision .	deep neural networks have demonstrated impressive performance on many machine-learning tasks such as image recognition .
this is because the time-ordering procedure in perturbation theory does not interfere with the partial integration of spatial integrals employed in the cyclicity prop erty .	furthermore , the manipulation with star products in perturbation theory should not interfere with the time-ordering procedure .
nonetheless studies have shown that extensions still require many permissions .	however a good number of studies have shown that many extensions still request too many permissions .
in recent years , there are many authors to study the fractional boundary value problems and the kirchhoff equations , and obtain numerous important results .	in the past few decades , many important results on the fractional boundary value problems and the kirchhoff equations have been obtained .
recently , with the popularization of social networks , social-trust based recommendation has recently been proposed to improve recommendation accuracy .	recently , with the popularity of social networks , social-trust based recommendation has recently been proposed to improve recommendation accuracy .
the generated events are passed through a simulation of the atlas detector .	the generator-level events are then passed through a geant 4 simulation of the atlas detector .
deep convolutional neural networks have shown tremendous success in a variety of computer vision tasks , such as image classification .	deep neural networks have been significantly successful in many artificial intelligence tasks such as im- age classification .
consequently in this work , we consider an structured variational family known as sparse gaussian process .	consequently , we adopt a structured approximation based on sparse gaussian process .
the simplest case in the well established fem is the use of linear hat functions .	firstly , there is the well established fem where , in the simplest case , linear hat functions are chosen .
simulation studies in show that the queue size feedback in rcp , can cause the queue to be less accurately controlled .	early results in show that the presence of queue feedback in rcp may lead to less accurate control over the queue size .
model agnostic meta-learning is a meta-learning framework for fewshot learning .	model-agnostic meta-learning , is an algorithm for meta-learning , especially effective for few-shot learning .
we can also suppose that β is in regular form .	that is , we can compute the canonical reduction system of β .
deep learning has led to significant improvements in many computer vision tasks such as image classification .	convolutional neural networks have achieved tremendous progress on many pattern recognition tasks , especially large-scale images recognition problems .
for evaluation , we use the well known action recognition dataset ucf101 .	we consider one real world example of action recognition task based on the standard ucf-101 benchmark .
hmms are especially known for their application in temporal pattern recognition such as speech , handwriting , gesture recognition .	hmms have long been among the main tools used for sequence modelling in voice recognition and hand-writing recognition .
the cascade classifier using haar feature , frequently used in face detection and object detection , can get fast detection performance .	haar-like feature based method is used for face detection because of its higher accuracy and faster execution .
similar to siamfc , in goturn tracker , the motion between successive frames is predicted using a deep regression network .	similarly to siamfc , in goturn tracker , the motion between successive frames is predicted using a deep regression network .
in particular , it is assumed that the probability density functions of all classes are gaussian with identical covariance matrix but with different means .	in particular , it is assumed that the probability density functions of all classes are gaussian with identical covariance matrices , but with different means .
recently , deep convolutional neural networks have achieved great successes in computer vision topics such as image classification .	deep neural networks achieve impressive results on many computer vision tasks such as image recognition .
recent work by dunn explores how much information remains on a host after a virtual machine has shut down as well as various methods for eliminating it .	recent work by dunn explores how much information remains on a host after a virtual machine has shut down , yet the hypervisor remains active , as well as various methods for eliminating it .
peng et al improved the performance of idt by increasing the codebook size and fusing multiple coding methods .	peng et al further improved the performance of dense trajectory by increasing the codebook sizes and fusing multiple coding methods .
the evolution equation for director is of viscoelastic type .	it is shown that the evolution equation for director is also viscoelastic .
the ordinate is the ratio of the bh mass as obtained from ground-based data to that obtained with hst kinematic data included .	the ordinate is the radius in logarithmic scale and the abscissa is the azimuthal angle and shown for two periods , or 0 720 degree , to delineate spiral arms .
jaderberg et al propose a module called spatial transformer , which allows the network to actively spatially transform feature maps conditioned on themselves without explicit supervision .	in , jaderberg et al introduced spatial transformer module that can be inserted into a standard neural network to perform the spatial manipulation of data within the network .
a natural question that arises is whether this shock is an artifact of the hydrodynamic limit or whether , under some specific conditions , the original asep does display some singularity at the microscopic scale .	a natural question that arises is whether this shock is an artifact of the hydrodynamic limit or if , under some specific conditions , the original asep does display some singularity at the microscopic scale .
pulsar is the rotational neutron star that contains a small remnant of the lec after supernova .	a pulsar is a rapidly rotating neutron star that emits highly directional radiation .
we perform a non-trivial adaptation of the algorithm from chang et al to devise a globally optimizing policy update scheme .	we perform a non-trivial adaptation of the algorithm from chang et al to our setting of optimizing cpt-value in mdps .
a complete survey in the area of control of truck and trailer systems can be found in .	a detailed survey on the various control strategies for the backward motion of a mobile robot with trailers can be found in .
the milky way is the most evolved galaxy of our sample , therefore its gas content is lower and its h ii regions are more metal-rich .	the milky way is a large spiral and its evolution is different from the average one not only quantitatively , but also qualitatively in some cases .
in cases where the mass parameter does not induce a gauging , the theory is called a massive supergravity .	in supergravity it is a reasonable demand that the stru ture .
recently , deep convolutional neural networks have taken the computer vision field by storm , significantly improving the state-of-the-art performances in many visual tasks , such as face recognition .	recently , deep learning models , especially convolutional neural networks , have revolutionized various machine learning tasks with gridlike input data , such as image classification .
the higgs boson is the only sm particle that has not yet been observed .	if the higgs boson is a fundamental scalar , its mass has to be protected .
in recent years , deep learning techniques have achieved exceptional results in many domains such as computer vision and natural language processing .	convolutional neural networks have seen tremendous success across different problems including image classification .
recently , the bicep2-experiment announced the discovery of a non-zero signal of primordial gravitational waves in the b-mode power spectrum .	recently , the bicep2 collaboration has discovered the primordial b-mode polarization of the cosmic microwave background .
deep neural networks have been showing impressive performance in a variety of applications in multiple domains .	recently deep neural networks have attained impressive performance in many fields such as image classification .
this efficiency is less than one because there is a systematic shift of reconstructed event positions away from the center of the detector as discussed in section 4 .	although its efficiency is the same for both fermions and bosons , the protocol itself is slightly different depending on the nature of the particles .
recently , bai et al modified the approach in rao et al and turned it to a fully moments based procedure .	in a recent work , a modification of the procedure in rao et al is proposed to get a direct moments estimator based on the sample moments .
deep neural networks have demonstrated impressive performance on many hard perception problems .	recently , deep convolutional neural networks have attracted a lot of attention in visual recognition due to its good performance .
in , gromov defined an analogous filling radius for a closed riemannian manifold .	the filling radius was originally defined by gromov for riemannian manifolds .
they find numerous applications in many domains of physics ranging from high energy physics and cosmology models .	these structures have been investigated for more than 40 years , and they find a myriad of applications in high energy and condensed matter physics .
a cosmological constant is the simplest model of dark energy , but no natural explanation for the origin of it can be given .	generally , the cosmological constant is a decreasing function of time .
the above example captures the essence of the general result for the mimo channels , given by the following theorem .	we will generalize the above example to the case of general mimo channels by using the following power-control for the feedback channel .
deep learning models have defied several state-ofthe-art techniques in tasks such as image recognition .	deep learning models have achieved remarkable success in computer vision .
it is significant that for relaxation systems a numerical scheme must possess a discrete analogy to the continuous asymptotic limit , because any scheme violating the correct asymptotic limit leads to spurious or poor solutions .	it is significant that a numerical scheme for relaxation systems must possess a discrete analogy to the continuous asymptotic limit , because any scheme violating the correct asymptotic limit leads to spurious or poor solutions .
a detailed description of the thermodynamics of the reissner-nordstrom-de sitter black hole is given in .	a description of thermodynamics and instantons of reissner-nordstrom-de sitter black holes are given in .
two-level systems possess a wide range of applications , for example , the semi-classical theory of laser beams , and so on .	in particular , two-level systems possess a wide range of applications , for example , in the semi-classical theory of laser beams , and so on .
neural networks have been shown to be extremely powerful in a wide range of machine learning tasks , evidenced by recent significant progress in tasks such as speech recognition .	deep neural network models have recently demonstrated impressive learning results in many visual and speech classification problems .
to incorporate long-range temporal structure using the two-stream networks , wang et al devised a temporal segment network that uses a sparse sampling scheme to extract short snippets over a long video sequence .	moreover , wang et al propose a temporal segment network to encode the longrange temporal structure over the whole video by feeding the network with several segments from one video .
furthermore , eclairs will provide the precise localization of the grb detected by glast , and therefore permit ground based follow-up observations of grb emitting at high-energies .	the complementary spectral coverage offered by eclairs will help in understanding the high-energy emission of the grb observed by glast .
in the segmentation scheme , this idea is combined with a graph-based method that has been introduced for the semiautomatic segmentation of the aorta and diffusion tensor imaging fiber bundle segmentation .	in the novel segmentation scheme , this idea is combined with a graph-based method that has been introduced for the semi-automatic segmentation of the aorta and diffusion tensor imaging fiber bundle segmentation .
it has been shown by sejdinovic et al that the distance covariance is an instance of hsic for an appropriate choice of kernels .	recently , hsic has been shown to be a class of kernel tests , sejdinovic et al , 2013 , where the tests are based on different combinations of distance-induced kernel pairs .
deep neural networks have achieved recordbreaking accuracy in many image classification tasks .	convolutional neural networks have achieved superior performance in many visual tasks , such as object classification and detection .
therefore , we also calculate the band structures by using the hse functional in order to get more accurate band gaps .	to account for the excitation aspect we add approximate quasiparticle corrections to the kohn-sham bands by applying the xc hybrid functional hse06 .
the first striking aspect is the perfect compensation of the non-dispersive terms , that is , the orbit errors are cancelled out in the analysis .	striking aspect is the rapid decline of brightness with distance from the agn .
generative adversarial networks form a popular framework for generating realistic samples from high-dimensional complex data distributions .	generative adversarial networks have been shown to capture complex and high-dimensional image data with numerous applications effectively .
we evaluate the performance of our slam system using the benchmarks rgb-d tum dataset .	we test the tracking and generalization performance of our motion module on the rgb-d tracking benchmark .
on the two-gap locus for the elliptic calogero-moser model .	on the eigenstates of the elliptic calogero-moser model .
recent advances in object detection on 2d images have achieved promising results .	recent methods have achieved encouraging progress for detecting objects in images .
temperature dependence of interface charge and reciprocal capacitance .	distance dependence of ferroelectric domain wall width .
now we proceed onto give examples of interval semigroup interval semirings .	we now proceed onto give examples of square interval .
graphene is a two-dimensional material made of carbon atoms arranged in a honeycomb structure .	graphene is a two-dimensional material consisting of a monolayer of carbon atom forming hexagonal lattices .
tations can be exploited using multitask learning , allowing us to learn from more data .	the multitask learning enables us to jointly analyze multiple tasks that are related to each other .
furthermore , the information needs to be gathered and processed at high rates , up to 1khz for fine force control .	the massive amounts of data generated by these taxels needs to be gathered and processed at high rates , up to 1khz for fine force control .
the asterisk denotes that the value was computed by eq .	the asterisk is the value discussed in detail in the text .
deep neural networks have demonstrated their success in many machine learning and computer vision applications , including image classification .	deep neural networks have proven to be an effective tool to classify and segment high dimensional data such as images .
the ordinate is the probability ke that a line exists as defined in the text .	the ordinate is the ratio of the core-sw component separation divided by the core-ne component separation .
the comparison of the obtained variational results with some available exact solutions shows good accuracy of our approach .	the comparison of variational calculations with some available exact results demonstrates good accuracy of our approximation .
to achieve better generalization we perform batch normalization to increase input variance .	between each convolutional layer and following non-linearity we use batch normalization .
steidel cc , adelberger kl , shapley ae , pettini m , dickinson m , giavalisco m .	vikhlinin a , mcnamara br , forman w , jones c , quintana h , hornstrup a .
machine learning models , especially deep neural networks , have been deployed prominently in many real-world applications , such as image classification .	convolutional neural networks have become the most popular method in many fields of computer vision , such as image recognition .
in this paper , we consider only the abelian theory .	in this paper , we have considered models with unbroken susy .
the spacetime consists of 4 dimensional black hole with an additional -dimensional sphere .	the spacetime is a static minkowski space , in contrast with the expansion in the einstein frame as shown by .
recent years have witnessed many breakthroughs in quantum simulation of strongly correlated many-body problems with dilute gases of ultracold particles .	recently , quantum dynamics of many-body systems attract interests of many researchers , and there has been impressive progress in both experiments and theories .
in order to bound the probability of we will then use the union bound .	then we will use the union bound to estimate the probability of .
the uniqueness is a direct application of the monotone class theorem .	uniqueness is a consequence of the last statement of the proposition .
recent progress in string theory has stimulated interest in solitons in noncommutative field theories .	quantum field theories on noncommutative space-times recently attracted much attention mainly due to their relation to string theory .
recent studies show that adversarially constructed perturbations , even if inperceptibly small , can dramatically decrease the accuracy of state-of-the-art models in image classification .	recent studies show that small adversarial pixel perturbations on images , even unnoticeable to the human eyes , can lead to misclassification by deep learning image classification .
next , we also evaluate our detector on the large objects dataset of without further tuning .	we also evaluate our detector on the large objects dataset of without further tuning .
then using the results given in we will consider the case when the tachyon field is still marginal however now also depends on the spatial coordinates .	in section we generalise the calculation given in to the tachyon boundary perturbation that depends on the spatial coordinates as well .
the compactifiby taking its closure in cn is called the topological compactification .	this explanation is called dynamical compactification .
in addition , generative adversarial networks may be applicable for generating synthetic medical images for data augmentation .	in particular , generative adversarial networks are suitable to enhance low dimensional information with details .
the emerging field of signal processing on graphs focuses on the extension of classical discrete signal processing techniques to the graph setting .	propelled by the desire of analyzing and processing data supported on irregular domains , there has been a growing interest in broadening the scope of traditional signal processing techniques to signals defined on graphs .
in recent years , deep convolutional neural networks have demonstrated dramatic improvements in performance for computer vision tasks such as object classification , detection , and segmentation .	recent methods based on convolutional neural networks have been shown to produce results of high accuracy for a wide range of challenging computer vision tasks like image recognition .
all calculations were performed using dft as implemented in the vienna ab-initio simulation package .	ab initio calculations were performed within the density-functional theory framework as implemented in the vasp code .
a computer consists of a control and processing unit and an unbounded memory .	a computer is a driven physical system , with irreversible operations of resetting and erasure .
the numerical results show that the adaptive construction method significantly reduces the correlations between the sampled data .	the results from the adaptive construction method have much smaller error bars and are consistent each other .

recently , birational mappings over finite fields have been investigated in terms of integrability .

recently bi-rational mappings over finite fields have been investigated in terms of integrability .

it was subsequently shown in , either do not have global scaling solutions , or the solutions are such that all their perturbations are redundant .

it had been shown in , either do not have scaling solutions , or the solutions are such that all their perturbations are redundant .

we 1the submillimeter array is a joint project between the smithsonian astrophys ical observatory and the academia sinica institute of astronomy and astrophysics and is funded by the smithsonian institution and the academia sinica .

the 5the submillimeter array is a joint project between the smithsonian astrophysical observatory and the academia sinica institute of astronomy and astrophysics , and is funded by the smithsonian institution and the academia sinica .

in appendix c , we computed the multipole moments for black saturn and orthogonal black di-ring cases as examples .

in appendix b , we compute the multipole moments for the black ring solutions with two angular momenta .

this may be also spelled out that vacuum is a most degenerate state of a system .

hence the flavour vacuum is a pure mixing condensate .

nilpotency is the basis to prove the undecidability of most of the undecidable properties of ca .

then nilpotency is the easiest problem among all decision problems on the limit set dynamics of stable ca and of ca with a unique subshift attractor .

convolutional neural networks have achieved superior performance in many visual tasks , such as object detection and segmentation .

more recently , convolutional neural networks have achieved unprecedented performance in a wide range of image classification problems .

dependence of afuv of paired galaxies on the separations .

dependence of afuv enhancement on galaxy stellar mass for spirals in s-s pairs .

capacity achieving non-linear dirty paper coding techniques have been proposed for pre-subtracting interference prior to transmission .

a capacity achieving nonlinear dirty paper coding technique has been proposed for presubtracting interference at the source prior to transmission .

generative adversarial networks define a framework for training a generative model by posing it as a minimax game .

generative adversarial networks consist of a deep generative model which is trained through a minimax game involving a competing generator and discriminator .

deep neural networks have made significant improvements in lots of computer vision tasks such as object recognition .

deep neural networks achieve impressive results on many computer vision tasks such as image recognition .

bert is a powerful language representation model , which is based on bidirectional transformer encoder .

bert uses a transformer encoder trained on masked language modeling and next-sentence prediction tasks .

yu et al integrated three types of features to construct a spatio-temporal representation , including pairwise joint distances , spatial joint coordinates , and temporal variations of joint locations .

yu et al used three categories of skeletal features , including pairwise joint distance , spatial joint coordinate , and temporal variation of joint locations , to construct a mixed representation .

iv , we summarize the results and discuss future work .

iii we discuss the physical parameters we will use and present the results .

deep neural networks have shown remarkable success in many domains , such as computer vision .

deep neural networks have demonstrated impressive performance on many machine-learning tasks such as image recognition .

this is because the time-ordering procedure in perturbation theory does not interfere with the partial integration of spatial integrals employed in the cyclicity prop erty .

furthermore , the manipulation with star products in perturbation theory should not interfere with the time-ordering procedure .

nonetheless studies have shown that extensions still require many permissions .

however a good number of studies have shown that many extensions still request too many permissions .

in recent years , there are many authors to study the fractional boundary value problems and the kirchhoff equations , and obtain numerous important results .

in the past few decades , many important results on the fractional boundary value problems and the kirchhoff equations have been obtained .

recently , with the popularization of social networks , social-trust based recommendation has recently been proposed to improve recommendation accuracy .

recently , with the popularity of social networks , social-trust based recommendation has recently been proposed to improve recommendation accuracy .

the generated events are passed through a simulation of the atlas detector .

the generator-level events are then passed through a geant 4 simulation of the atlas detector .

deep convolutional neural networks have shown tremendous success in a variety of computer vision tasks , such as image classification .

deep neural networks have been significantly successful in many artificial intelligence tasks such as im- age classification .

consequently in this work , we consider an structured variational family known as sparse gaussian process .

consequently , we adopt a structured approximation based on sparse gaussian process .

the simplest case in the well established fem is the use of linear hat functions .

firstly , there is the well established fem where , in the simplest case , linear hat functions are chosen .

simulation studies in show that the queue size feedback in rcp , can cause the queue to be less accurately controlled .

early results in show that the presence of queue feedback in rcp may lead to less accurate control over the queue size .

model agnostic meta-learning is a meta-learning framework for fewshot learning .

model-agnostic meta-learning , is an algorithm for meta-learning , especially effective for few-shot learning .

we can also suppose that β is in regular form .

that is , we can compute the canonical reduction system of β .

deep learning has led to significant improvements in many computer vision tasks such as image classification .

convolutional neural networks have achieved tremendous progress on many pattern recognition tasks , especially large-scale images recognition problems .

for evaluation , we use the well known action recognition dataset ucf101 .

we consider one real world example of action recognition task based on the standard ucf-101 benchmark .

hmms are especially known for their application in temporal pattern recognition such as speech , handwriting , gesture recognition .

hmms have long been among the main tools used for sequence modelling in voice recognition and hand-writing recognition .

the cascade classifier using haar feature , frequently used in face detection and object detection , can get fast detection performance .

haar-like feature based method is used for face detection because of its higher accuracy and faster execution .

similar to siamfc , in goturn tracker , the motion between successive frames is predicted using a deep regression network .

similarly to siamfc , in goturn tracker , the motion between successive frames is predicted using a deep regression network .

in particular , it is assumed that the probability density functions of all classes are gaussian with identical covariance matrix but with different means .

in particular , it is assumed that the probability density functions of all classes are gaussian with identical covariance matrices , but with different means .

recently , deep convolutional neural networks have achieved great successes in computer vision topics such as image classification .

deep neural networks achieve impressive results on many computer vision tasks such as image recognition .

recent work by dunn explores how much information remains on a host after a virtual machine has shut down as well as various methods for eliminating it .

recent work by dunn explores how much information remains on a host after a virtual machine has shut down , yet the hypervisor remains active , as well as various methods for eliminating it .

peng et al improved the performance of idt by increasing the codebook size and fusing multiple coding methods .

peng et al further improved the performance of dense trajectory by increasing the codebook sizes and fusing multiple coding methods .

the evolution equation for director is of viscoelastic type .

it is shown that the evolution equation for director is also viscoelastic .

the ordinate is the ratio of the bh mass as obtained from ground-based data to that obtained with hst kinematic data included .

the ordinate is the radius in logarithmic scale and the abscissa is the azimuthal angle and shown for two periods , or 0 720 degree , to delineate spiral arms .

jaderberg et al propose a module called spatial transformer , which allows the network to actively spatially transform feature maps conditioned on themselves without explicit supervision .

in , jaderberg et al introduced spatial transformer module that can be inserted into a standard neural network to perform the spatial manipulation of data within the network .

a natural question that arises is whether this shock is an artifact of the hydrodynamic limit or whether , under some specific conditions , the original asep does display some singularity at the microscopic scale .

a natural question that arises is whether this shock is an artifact of the hydrodynamic limit or if , under some specific conditions , the original asep does display some singularity at the microscopic scale .

pulsar is the rotational neutron star that contains a small remnant of the lec after supernova .

a pulsar is a rapidly rotating neutron star that emits highly directional radiation .

we perform a non-trivial adaptation of the algorithm from chang et al to devise a globally optimizing policy update scheme .

we perform a non-trivial adaptation of the algorithm from chang et al to our setting of optimizing cpt-value in mdps .

a complete survey in the area of control of truck and trailer systems can be found in .

a detailed survey on the various control strategies for the backward motion of a mobile robot with trailers can be found in .

the milky way is the most evolved galaxy of our sample , therefore its gas content is lower and its h ii regions are more metal-rich .

the milky way is a large spiral and its evolution is different from the average one not only quantitatively , but also qualitatively in some cases .

in cases where the mass parameter does not induce a gauging , the theory is called a massive supergravity .

in supergravity it is a reasonable demand that the stru ture .

recently , deep convolutional neural networks have taken the computer vision field by storm , significantly improving the state-of-the-art performances in many visual tasks , such as face recognition .

recently , deep learning models , especially convolutional neural networks , have revolutionized various machine learning tasks with gridlike input data , such as image classification .

the higgs boson is the only sm particle that has not yet been observed .

if the higgs boson is a fundamental scalar , its mass has to be protected .

in recent years , deep learning techniques have achieved exceptional results in many domains such as computer vision and natural language processing .

convolutional neural networks have seen tremendous success across different problems including image classification .

recently , the bicep2-experiment announced the discovery of a non-zero signal of primordial gravitational waves in the b-mode power spectrum .

recently , the bicep2 collaboration has discovered the primordial b-mode polarization of the cosmic microwave background .

deep neural networks have been showing impressive performance in a variety of applications in multiple domains .

recently deep neural networks have attained impressive performance in many fields such as image classification .

this efficiency is less than one because there is a systematic shift of reconstructed event positions away from the center of the detector as discussed in section 4 .

although its efficiency is the same for both fermions and bosons , the protocol itself is slightly different depending on the nature of the particles .

recently , bai et al modified the approach in rao et al and turned it to a fully moments based procedure .

in a recent work , a modification of the procedure in rao et al is proposed to get a direct moments estimator based on the sample moments .

deep neural networks have demonstrated impressive performance on many hard perception problems .

recently , deep convolutional neural networks have attracted a lot of attention in visual recognition due to its good performance .

in , gromov defined an analogous filling radius for a closed riemannian manifold .

the filling radius was originally defined by gromov for riemannian manifolds .

they find numerous applications in many domains of physics ranging from high energy physics and cosmology models .

these structures have been investigated for more than 40 years , and they find a myriad of applications in high energy and condensed matter physics .

a cosmological constant is the simplest model of dark energy , but no natural explanation for the origin of it can be given .

generally , the cosmological constant is a decreasing function of time .

the above example captures the essence of the general result for the mimo channels , given by the following theorem .

we will generalize the above example to the case of general mimo channels by using the following power-control for the feedback channel .

deep learning models have defied several state-ofthe-art techniques in tasks such as image recognition .

deep learning models have achieved remarkable success in computer vision .

it is significant that for relaxation systems a numerical scheme must possess a discrete analogy to the continuous asymptotic limit , because any scheme violating the correct asymptotic limit leads to spurious or poor solutions .

it is significant that a numerical scheme for relaxation systems must possess a discrete analogy to the continuous asymptotic limit , because any scheme violating the correct asymptotic limit leads to spurious or poor solutions .

a detailed description of the thermodynamics of the reissner-nordstrom-de sitter black hole is given in .

a description of thermodynamics and instantons of reissner-nordstrom-de sitter black holes are given in .

two-level systems possess a wide range of applications , for example , the semi-classical theory of laser beams , and so on .

in particular , two-level systems possess a wide range of applications , for example , in the semi-classical theory of laser beams , and so on .

neural networks have been shown to be extremely powerful in a wide range of machine learning tasks , evidenced by recent significant progress in tasks such as speech recognition .

deep neural network models have recently demonstrated impressive learning results in many visual and speech classification problems .

to incorporate long-range temporal structure using the two-stream networks , wang et al devised a temporal segment network that uses a sparse sampling scheme to extract short snippets over a long video sequence .

moreover , wang et al propose a temporal segment network to encode the longrange temporal structure over the whole video by feeding the network with several segments from one video .

furthermore , eclairs will provide the precise localization of the grb detected by glast , and therefore permit ground based follow-up observations of grb emitting at high-energies .

the complementary spectral coverage offered by eclairs will help in understanding the high-energy emission of the grb observed by glast .

in the segmentation scheme , this idea is combined with a graph-based method that has been introduced for the semiautomatic segmentation of the aorta and diffusion tensor imaging fiber bundle segmentation .

in the novel segmentation scheme , this idea is combined with a graph-based method that has been introduced for the semi-automatic segmentation of the aorta and diffusion tensor imaging fiber bundle segmentation .

it has been shown by sejdinovic et al that the distance covariance is an instance of hsic for an appropriate choice of kernels .

recently , hsic has been shown to be a class of kernel tests , sejdinovic et al , 2013 , where the tests are based on different combinations of distance-induced kernel pairs .

deep neural networks have achieved recordbreaking accuracy in many image classification tasks .

convolutional neural networks have achieved superior performance in many visual tasks , such as object classification and detection .

therefore , we also calculate the band structures by using the hse functional in order to get more accurate band gaps .

to account for the excitation aspect we add approximate quasiparticle corrections to the kohn-sham bands by applying the xc hybrid functional hse06 .

the first striking aspect is the perfect compensation of the non-dispersive terms , that is , the orbit errors are cancelled out in the analysis .

striking aspect is the rapid decline of brightness with distance from the agn .

generative adversarial networks form a popular framework for generating realistic samples from high-dimensional complex data distributions .

generative adversarial networks have been shown to capture complex and high-dimensional image data with numerous applications effectively .

we evaluate the performance of our slam system using the benchmarks rgb-d tum dataset .

we test the tracking and generalization performance of our motion module on the rgb-d tracking benchmark .

on the two-gap locus for the elliptic calogero-moser model .

on the eigenstates of the elliptic calogero-moser model .

recent advances in object detection on 2d images have achieved promising results .

recent methods have achieved encouraging progress for detecting objects in images .

temperature dependence of interface charge and reciprocal capacitance .

distance dependence of ferroelectric domain wall width .

now we proceed onto give examples of interval semigroup interval semirings .

we now proceed onto give examples of square interval .

graphene is a two-dimensional material made of carbon atoms arranged in a honeycomb structure .

graphene is a two-dimensional material consisting of a monolayer of carbon atom forming hexagonal lattices .

tations can be exploited using multitask learning , allowing us to learn from more data .

the multitask learning enables us to jointly analyze multiple tasks that are related to each other .

furthermore , the information needs to be gathered and processed at high rates , up to 1khz for fine force control .

the massive amounts of data generated by these taxels needs to be gathered and processed at high rates , up to 1khz for fine force control .

the asterisk denotes that the value was computed by eq .

the asterisk is the value discussed in detail in the text .

deep neural networks have demonstrated their success in many machine learning and computer vision applications , including image classification .

deep neural networks have proven to be an effective tool to classify and segment high dimensional data such as images .

the ordinate is the probability ke that a line exists as defined in the text .

the ordinate is the ratio of the core-sw component separation divided by the core-ne component separation .

the comparison of the obtained variational results with some available exact solutions shows good accuracy of our approach .

the comparison of variational calculations with some available exact results demonstrates good accuracy of our approximation .

to achieve better generalization we perform batch normalization to increase input variance .

between each convolutional layer and following non-linearity we use batch normalization .

steidel cc , adelberger kl , shapley ae , pettini m , dickinson m , giavalisco m .

vikhlinin a , mcnamara br , forman w , jones c , quintana h , hornstrup a .

machine learning models , especially deep neural networks , have been deployed prominently in many real-world applications , such as image classification .

convolutional neural networks have become the most popular method in many fields of computer vision , such as image recognition .

in this paper , we consider only the abelian theory .

in this paper , we have considered models with unbroken susy .

the spacetime consists of 4 dimensional black hole with an additional -dimensional sphere .

the spacetime is a static minkowski space , in contrast with the expansion in the einstein frame as shown by .

recent years have witnessed many breakthroughs in quantum simulation of strongly correlated many-body problems with dilute gases of ultracold particles .

recently , quantum dynamics of many-body systems attract interests of many researchers , and there has been impressive progress in both experiments and theories .

in order to bound the probability of we will then use the union bound .

then we will use the union bound to estimate the probability of .

the uniqueness is a direct application of the monotone class theorem .

uniqueness is a consequence of the last statement of the proposition .

recent progress in string theory has stimulated interest in solitons in noncommutative field theories .

quantum field theories on noncommutative space-times recently attracted much attention mainly due to their relation to string theory .

recent studies show that adversarially constructed perturbations , even if inperceptibly small , can dramatically decrease the accuracy of state-of-the-art models in image classification .

recent studies show that small adversarial pixel perturbations on images , even unnoticeable to the human eyes , can lead to misclassification by deep learning image classification .

next , we also evaluate our detector on the large objects dataset of without further tuning .

we also evaluate our detector on the large objects dataset of without further tuning .

then using the results given in we will consider the case when the tachyon field is still marginal however now also depends on the spatial coordinates .

in section we generalise the calculation given in to the tachyon boundary perturbation that depends on the spatial coordinates as well .

the compactifiby taking its closure in cn is called the topological compactification .

this explanation is called dynamical compactification .

in addition , generative adversarial networks may be applicable for generating synthetic medical images for data augmentation .

in particular , generative adversarial networks are suitable to enhance low dimensional information with details .

the emerging field of signal processing on graphs focuses on the extension of classical discrete signal processing techniques to the graph setting .

propelled by the desire of analyzing and processing data supported on irregular domains , there has been a growing interest in broadening the scope of traditional signal processing techniques to signals defined on graphs .

in recent years , deep convolutional neural networks have demonstrated dramatic improvements in performance for computer vision tasks such as object classification , detection , and segmentation .

recent methods based on convolutional neural networks have been shown to produce results of high accuracy for a wide range of challenging computer vision tasks like image recognition .

all calculations were performed using dft as implemented in the vienna ab-initio simulation package .

ab initio calculations were performed within the density-functional theory framework as implemented in the vasp code .

a computer consists of a control and processing unit and an unbounded memory .

a computer is a driven physical system , with irreversible operations of resetting and erasure .

the numerical results show that the adaptive construction method significantly reduces the correlations between the sampled data .

the results from the adaptive construction method have much smaller error bars and are consistent each other .