HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
the above discussion shows that this is not true in general .	the following example shows that this is not possible .
the exceptional divisor is the inverse image f of e in x .	so the exceptional divisor is a p1 bundle over the base p1 parametrised by z1 , z4 , ie it is a hirzebruch surface .
data reduction was carried out following standard procedures within the common astronomy software application .	data were calibrated in the standard way using the common astronomy software applications package .
the detector response in larsoft is modelled according to the geant4 toolkit for the simulation of the passage of particles through matter .	the particle propagation and their energy deposition in the detector are simulated using the nexus software .
the method of shifting the value of t background in the conformally invariant manner by switching on parameters like wilson lines is called marginal deformation .	a move which factors as a finite composition of elementary moves is called an elementary deformation .
we adopt the linearized power flow model , which is widely used as an approximation for more realistic nonlinear ac power model .	we adopt the linearized dc power flow model , which is widely used as an approximation for the non-linear ac power flow model .
here we extend this result from categories to generalized multicategories .	here we meet algebras for generalized multicategories .
the cryostat is a steel vessel with a copper lining used primarily to reduce the gamma radiation from the steel vessel .	the cryostat consists of a room temperature vacuum shield , a 77 k thermal shield anchored to a liquid nitrogen dewar , and a 4 k liquid helium dewar .
the strategy for both algorithms is to construct a 5-approximate solution using the algorithm from and to perform subsequent local improvements to that initial dominating set .	the strategy in both cases is to construct a 5-approximate solution using the algorithm from , and then perform local improvements to that initial dominating set .
on a practical point of view , generation of random lambda terms is the core of debugging functional programs using random tests , since we are able to generate closed typable terms following a uniform distribution .	from the practical point of view , generation of random λ-terms is the core of debugging functional programs using random tests , since we are able to generate closed typable terms following a uniform distribution .
in it is argued that the recognition of the lie group structure of the mobility space may help planning methods based on searching in the configurations space .	in it is argued that the incorporation of the lie group structure which characterizes the mobility space of an embodied agent may be helpful for planning methods based on searching in the configurations space .
the bigon is the dotted line joining the third bridge to the quadrilateral thickened .	a bigon of t is a region bounded by two segments .
the morris-lecar model is a planar system that models the voltage oscillations in the barnacle giant muscle fiber .	the morris-lecar model is a planar conductance-based model , originally developed to model various oscillations observed in barnacle muscle .
the computation of filters is done with the scikit-learn fast ica implementation .	archetypal analysis is performed using the spams software package .
frames where introduced by duffin and schaeffer in their work on nonharmonic fourier series .	frames , which are generalizations of bases , were introduced in the context of nonharmonic fourier series by duffin and schaeffer , .
as discussed by , a concept hierarchy forms a partially ordered set , which is a set x equipped with reflexive , transitive , and antisymmetric binary relations .	as discussed by , a concept hierarchy forms a partially ordered set , which is a set s equipped with reflexive , transitive , and antisymmetric binary relations .
many linearly convergent stochastic methods , such as sdca , have been introduced and shown to outperform the standard first order methods under mild assumptions .	many linearly convergent proximal methods such as , saga , have been introduced and shown to outperform standard first-order methods under certain regularity assumptions .
convolutional neural networks have achieved remarkable successes for various tasks , such as object recognition and so on .	onvolutional neural networks have achieved remarkable performance on vision problems such as image classification .
these parameters are adapted via stochastic gradient descent on a surrogate loss function related to the misclassification error , with gradients computed efficiently via the backpropagation algorithm .	once a suitable cost function has been defined , the derivatives of the cost with respect to the model parameters are found using the backpropagation algorithm and parameters are updated using stochastic gradient descent .
in their notable work culler and shalen established a method to construct essential surfaces in a 3-manifold from information of the s l 2 -character variety of its fundamental group .	in , culler and shalen defined the sl 2 character variety x sl2 of a manifold m whose fundamental group is finitely generated .
since low energy properties of the ferromagnetic spinor bec are dominated by the three collective excitations , our results would be useful for understanding dynamical properties in this superfluid phase .	our results would be useful for understanding excitation properties of spinor becs , as well as the anomalous tunneling phenomenon in bose superfluids .
most stars are born in large clusters numbering hundreds or even thousands of stars .	most stars are born within rich clusters of many hundreds to many thousands of stars .
recently , end-to-end neural machine translation models have achieved notable success .	neural machine translation has enjoyed impressive success in most large-scale translation tasks .
over the last two decades , the lattice boltzmann method has become a prominent tool in computational fluid dynamics , to cite but a few .	in recent two decades the lattice boltzmann method has been becoming a powerful tool for simulating complex systems .
deep neural networks have demonstrated stateof-the-art and sometimes human-competitive performance in numerous vision-related tasks .	convolutional neural networks , trained on large scale data , have significantly advanced the state-of-theart on traditional vision problems such as object recognition .
for the iv dataset , we follow the standard evaluation criterion to use the average precision as the measure .	we use the standard mean intersection-over-union score as the evaluation metric for both datasets .
as the phase space for the 2-sphere consists of a point , the wavefunction in this formulation is trivial .	the phase space a consist of the solutions of eq .
thus conventional dcf trackers can perform at more than 100 fps , which is significant for real-time applications .	conventional dcf trackers such as mosse , csk and kcf can perform at more than 100 fps .
since interval-valued fuzzy sets are widely studied and used , we describe briefly the work of gorzalczany on approximate reasoning .	since interval-valued fuzzy sets are widely studied and used , we describe briefly the work of gorzalczany on approximate reasoning in 1973 .
however , this structure will deteriorate the preamble detection performance over multipath channels .	in fact , a 0db echo channel with certain delay spread will entirely destroy the preamble detection .
we adopt a latency-oriented performance metric , called the normalized delivery time , introduced in .	we adopt the normalized delivery time , introduced in , as the performance metric of interest .
overlaid is the fit with an absorbed power law model described in the text .	overlaid is the exclusion result published in ref .
deep neural networks have shown great success in computer vision and natural language processing tasks .	deep neural networks show dramatically accurate results on challenging tasks .
the transverse gluon momentum characterizing the transition scale between the two regimes is called saturation momentum and is defined below .	the momentum qs at which this mechanism sets in is known as the saturation momentum .
sharing parameters between related tasks to improve joint performance is prominent in multitask learning .	in multitask learning , auxiliary data sets are harnessed to improve overall performance by exploiting regularities present across tasks .
advances in deep learning have led to tremendous success in a wide variety of applications in visual and audio perception such as image classification .	deep convolutional neural networks have achieved great success on many tasks across a variety of domains , such as vision .
thus we have proved the following theorem .	the converse direction is covered by the following theorem .
hydrogen is the main opacity source in the photospheres of o stars .	hydrogen is the chosen reference element since it is the most common element in the universe as a whole and that it normally dominates the continuous opacity in the formation of the stellar spectra .
the specific model to be 15 discussed here is the pair hidden markov model .	specific to our model is the explicit treatment of the mesonic degrees of freedom including retardation .
later , meeks and rosenberg generalized this result to complete , embedded minimal surfaces with positive injectivity radius in r 3 in .	after this , meeks and rosenberg proved that if σ is a complete embedded minimal surface in r 3 which has positive injectivity radius , then σ is proper , .
the functor dmb is an equivalence of triangulated monoidal categories .	this construction is compatible with composition of morphisms .
a qubit is a unit vector in the hilbert space c2 .	the qubit consists of the last two vectors .
the behavior of the color singlet free energy in the deconfined phase has been studied in coulomb gauge .	the color adjoint correlator in coulomb gauge has been studied in pure gauge theory .
generative adversarial networks have emerged as a powerful framework for learning generative models of arbitrarily complex data distributions .	generative adversarial networks have gained significant popularity in the machine learning community recently as it provides a novel and easy way to learn generative models .
these methods sometimes use multiple individual-tailored decisions to choose video portions for the summary and often rely on the determinantal point process in order to increase the diversity of selected video subsets .	these include method which use multiple man-tailored decisions to choose video portions for the summary and methods relying on the determinatal point process to increase the diversity of selected video subsets .
to speed up the sr process , dong et al extracted features directly from the lr image , that also achieved better performance compared to processing the upscaled lr image through bicubic interpolation .	to speed up the sr process , dong et al extracted features directly from the lr image , that also achieved better performance compared to processing the upscaled lr image through bicubic .
recently , cnns have been successfully applied to a variety of applications , including image classification .	cnns have been embraced across a wide array of fields , such as recommendation systems .
our proposed model is trained using the adam optimizer , with mini-batch size 30 .	we use the adam optimizer using a fixed batch size of 16 during training .
in particular , this property is inconsistent with a physical picture for parton branching at strong coupling .	in fact , the absence of the collinear singularity at strong coupling has been recurrently observed in the literature .
his recent research interests include cross layer design , interference management in interference network , and embedded system design .	his research interests include mimo communications with limited feedback , relay-assisted communications , and interference mitigation techniques .
we used the popular moses toolkit to train our smt system for the two language pairs .	we used the moses system as our baseline phrase-based smt system .
clearly the vacuum is a minimum of the potential in these directions , as confirmed , for all field directions , by a calculation of the eigenvalues of the mass matrix .	the vacuum is a dual superconductor in the confined phase and becomes trivial in the deconfined one .
by duality , there is a similar correspondence between right bol loops and right bol quasigroups .	duality is a deep concept in statistical mechanics and in quantum field theory .
in the past few years , convolutional neural networks have made tremendous progress in learning image features and solving various computer vision tasks .	for the past several years , deep convolution neural networks have found their extensive applications in image processing such as image classification , and so forth .
the data were calibrated in the common astronomy software application with the supplied calibration script .	the data were edited and calibrated following standard procedures within the common astronomy software application .
we consider a wireless network and we follow definitions given in .	we consider a wireless network model and we follow definitions given in .
in , socher et al proposed an unfolding recursive autoencoder for paraphrase identification .	socher et al present an approach based on recursive autoencoders for paraphrase detection .
deep convolutional neural networks have achieved great success in computer vision related tasks such as image classification , and so on .	convolutional neural networks have led to leap-forward in a large number of computer vision applications .
to accelerate convergence , we add batch normalization after each convolution and learn the scale and shift parameters during training .	after the training of each layer , we use batch normalization to avoid the internal covariate shift problem .
cosmic strings are effectively one-dimensional topological defects which may form at a phase transition in the early universe .	cosmic strings are a special kind of topological defects , which could have been formed in a symmetry breaking phase transition in the early universe .
however , one of the pilot agents failed to orre tly pro ess the mission statement .	however , due to an unexpe ted sensor failure , one of the atta kers failed to sense the way-point .
otherwise , the orbit contains only one element and is called a fixed orbit .	if the orbit is a horseshoe where the inner part has negative and the outer part positive sense of rotation , the soliton is unstable and desintegrates very quickly .
volatility is a measure of the uncertainty of price movements and is the standard way to characterize risk .	in the financial context , this observable is called volatility .
two of the most commonly used and efficient approaches are vae and generative adversarial networks .	variational autoencoders and generative adversarial networks have emerged as two of the most effective frameworks .
we compare the proposed method with 10 recent state-ofthe-art methods on aforementioned datasets , which include gmr .	finally , we compare our rds network with other state-of-the-art methods on five public sod datasets , hku-is .
recently , deep convolutional neural networks have achieved great successes in computer vision topics such as image classification .	deep neural networks have made great strides in many computer vision tasks such as image classification .
kim et al increased the network depth in vdsr by using gradient clipping , skip connection , or recursive-supervision to ease the difficulty of training deep network .	then , the drcn kim et al proposed relieved the difficulty of deep network training by using gradient clips , skipping connections and recursive supervision .
each activation layer is preceded by a layer of batch normalization .	the first four layers are followed by a batch normalization activation function .
standard multi-task learning aims at learning multiple tasks in a joint manner .	hence , multi-task learning employs sharing of fundamental knowledge across tasks .
this explains the strong anisotropy of the magnitude of the effect around the fermi surface .	the high energy dispersion does not extrapolate to the fermi surface crossing .
the immersed boundary method is a flexible approach for the treatment of moving boundaries with complex geometry .	the immersed boundary method is a very popular numerical approach in the simulation of complex and moving boundary problems .
it should be plausible that this is the case , at least if we exclude a finite number of values of the floquet exponents .	it is very plausible that this is the case .
deep feedforward neural networks , with multiple hidden layers , have achieved remarkable performance across many domains .	deep neural networks have been evolved to powerful predictive models with remarkable performance on computer vision tasks .
the connection to topological interference management problems follows from .	when the channel coefficients are fixed the topological interference management problem is shown in .
the approach thus needs only two database scans .	this approach needs only one pass of the database .
dropout is one of the most effective and widely used regularization techniques for neural networks .	dropconnect , is the method used for regularizing deep neural networks .
exchange-correlation energies are taken into account by the generalized gradient approximation using perdew-burke-ernzerhof functional .	the exchange-correlation functional is modeled in the generalized gradient approximation with the perdew-burke-ernzerhof realization .
deep networks have been successfully applied in various computer vision tasks , including image classification .	deep convolutional neural networks have been successful in many computer vision tasks including image classification .
deep convolutional neural networks have performed impressively on very large-scale image recognition problems .	deep convolutional neural networks have made significant breakthroughs in many visual understanding tasks including image classification .
the other known general criteria for subnormality , require the operator in question to have an invariant domain .	the other known criteria for subnormality require the operator in question to have an invariant domain .
zhu et al proposed a lstm network with a mixed-norm regularization term to cost functions in order to learn the co-occurrence of discriminative features from skeletal data .	zhu et al proposed a deep lstm network to model the inherent correlations among skeleton joints and the temporal dynamics in various actions .
gatenby and vincent adopted a game theory approach influenced by population dynamics to study tumour-host interactions in colorectal carcinogenesis .	gatenby and vincent adopted a game theory model heavily influenced by population dynamics to investigate the influence of the tumour-host interface in colorectal carcinogenesis .
introduction the longstanding problem of the generation of turbulence in various hydrodynamically stable situations has found a solution in recent years with the mhd shear flow instability , also called magnetorotational instability .	the other instability is the landau instability , which is applicable to the case with dissipation .
nt a dipolar condensate is a condensate possessing the dipole-dipole interactions , in addition to the usual swave contact interaction .	the pancake dipolar condensate is the first example of a weakly interacting gas , where the spectrum has a roton-maxon form .
convolutional neural networks have shown significant success in challenging tasks in image classification and recognition .	convolutional neural networks have achieved impressive state-of-the-art results on image classification .
gravity is a weak interaction , even at the enormous energies usually conceived for inflation , so the increment from each new pair is minuscule .	since gravity is a purely attractive force , and since the fluctuations on scales of the cmb anisotropies were small in amplitude when the anisotropies were generated , the fluctuations had to have been very small in the early universe .
these include the mutual coherence and the restricted isometry constants .	these include the mutual coherence and restricted isometery property .
the simplest of these constructions is the protocol for a secure hadamard gate .	in all of these constructions , the result is a seiberg-witten floer homology that can be shown to be of the form advertised above .
for the gmu component , we use batch normalization applied to each modality matrix .	for regularization purposes we have included dropout and batch normalization in each residual block .
possible-world semantics for autoepistemic logic .	a semantical approach to nonmonotonic logics .
in the past decade , grids have evolved as the infrastructure for delivering high-performance services for compute and data-intensive scientific applications .	in the past decade , grids have evolved as the infrastructure for delivering high-performance service for compute and data-intensive scientific applications .
the recent papers on compressive sensing provide the missing theoretical guarantees -conditions for exact recovery and error bounds when exact recovery is not possible .	the papers on compressive sensing from 2005 provide the missing theoretical guarantees -conditions for exact recovery and error bounds when exact recovery is not possible .
deep neural networks play an increasingly central role in a wide variety of state of the art machine learning applications .	in recent years , deep learning has emerged as the dominant solution showing remarkable success in a wide spectrum of artificial intelligence applications .
the lagrangian is the basis of our control theory , since it allows the derivation of the equations to be fulfilled by the control field .	the lagrangian for this is a natural generalisation of , with the addition of supersymmetry .
deep learning models have accomplished superior performance in several machine learning problems , which use either visual or audio sources .	convolutional neural networks have recently demonstrated impressive performance on various computer vision tasks such as semantic image segmentation and alike .
in recent years , deep learning techniques have achieved exceptional results in many domains such as computer vision and natural language processing .	recently , deep neural networks have led to significant improvement in several machine learning domains , from speech recognition to computer vision and machine translation .
object detection with top-down segmentation feedback for the detection sub-network , we use the state-ofthe-art fastr-cnn .	we compare craft with state-of-the-art detectors under the two-step detection framework , which are fast r-cnn .
recognizability of graph and pattern languages .	finite-state recognizability of graph properties .
the spectra were fitted in xspec with a powerlaw plus multiple gaussian model , including fits for both emission lines and absorption lines .	the spectra were fitted in xspec with the mekal plasma emission code , absorbed by the phabs photoelectric absorption code .
in the monte carlo language this is known as thermalization .	per forming the monte carlo iterations to obtain such independent field configurations is called thermalization .

the above discussion shows that this is not true in general .

the following example shows that this is not possible .

the exceptional divisor is the inverse image f of e in x .

so the exceptional divisor is a p1 bundle over the base p1 parametrised by z1 , z4 , ie it is a hirzebruch surface .

data reduction was carried out following standard procedures within the common astronomy software application .

data were calibrated in the standard way using the common astronomy software applications package .

the detector response in larsoft is modelled according to the geant4 toolkit for the simulation of the passage of particles through matter .

the particle propagation and their energy deposition in the detector are simulated using the nexus software .

the method of shifting the value of t background in the conformally invariant manner by switching on parameters like wilson lines is called marginal deformation .

a move which factors as a finite composition of elementary moves is called an elementary deformation .

we adopt the linearized power flow model , which is widely used as an approximation for more realistic nonlinear ac power model .

we adopt the linearized dc power flow model , which is widely used as an approximation for the non-linear ac power flow model .

here we extend this result from categories to generalized multicategories .

here we meet algebras for generalized multicategories .

the cryostat is a steel vessel with a copper lining used primarily to reduce the gamma radiation from the steel vessel .

the cryostat consists of a room temperature vacuum shield , a 77 k thermal shield anchored to a liquid nitrogen dewar , and a 4 k liquid helium dewar .

the strategy for both algorithms is to construct a 5-approximate solution using the algorithm from and to perform subsequent local improvements to that initial dominating set .

the strategy in both cases is to construct a 5-approximate solution using the algorithm from , and then perform local improvements to that initial dominating set .

on a practical point of view , generation of random lambda terms is the core of debugging functional programs using random tests , since we are able to generate closed typable terms following a uniform distribution .

from the practical point of view , generation of random λ-terms is the core of debugging functional programs using random tests , since we are able to generate closed typable terms following a uniform distribution .

in it is argued that the recognition of the lie group structure of the mobility space may help planning methods based on searching in the configurations space .

in it is argued that the incorporation of the lie group structure which characterizes the mobility space of an embodied agent may be helpful for planning methods based on searching in the configurations space .

the bigon is the dotted line joining the third bridge to the quadrilateral thickened .

a bigon of t is a region bounded by two segments .

the morris-lecar model is a planar system that models the voltage oscillations in the barnacle giant muscle fiber .

the morris-lecar model is a planar conductance-based model , originally developed to model various oscillations observed in barnacle muscle .

the computation of filters is done with the scikit-learn fast ica implementation .

archetypal analysis is performed using the spams software package .

frames where introduced by duffin and schaeffer in their work on nonharmonic fourier series .

frames , which are generalizations of bases , were introduced in the context of nonharmonic fourier series by duffin and schaeffer , .

as discussed by , a concept hierarchy forms a partially ordered set , which is a set x equipped with reflexive , transitive , and antisymmetric binary relations .

as discussed by , a concept hierarchy forms a partially ordered set , which is a set s equipped with reflexive , transitive , and antisymmetric binary relations .

many linearly convergent stochastic methods , such as sdca , have been introduced and shown to outperform the standard first order methods under mild assumptions .

many linearly convergent proximal methods such as , saga , have been introduced and shown to outperform standard first-order methods under certain regularity assumptions .

convolutional neural networks have achieved remarkable successes for various tasks , such as object recognition and so on .

onvolutional neural networks have achieved remarkable performance on vision problems such as image classification .

these parameters are adapted via stochastic gradient descent on a surrogate loss function related to the misclassification error , with gradients computed efficiently via the backpropagation algorithm .

once a suitable cost function has been defined , the derivatives of the cost with respect to the model parameters are found using the backpropagation algorithm and parameters are updated using stochastic gradient descent .

in their notable work culler and shalen established a method to construct essential surfaces in a 3-manifold from information of the s l 2 -character variety of its fundamental group .

in , culler and shalen defined the sl 2 character variety x sl2 of a manifold m whose fundamental group is finitely generated .

since low energy properties of the ferromagnetic spinor bec are dominated by the three collective excitations , our results would be useful for understanding dynamical properties in this superfluid phase .

our results would be useful for understanding excitation properties of spinor becs , as well as the anomalous tunneling phenomenon in bose superfluids .

most stars are born in large clusters numbering hundreds or even thousands of stars .

most stars are born within rich clusters of many hundreds to many thousands of stars .

recently , end-to-end neural machine translation models have achieved notable success .

neural machine translation has enjoyed impressive success in most large-scale translation tasks .

over the last two decades , the lattice boltzmann method has become a prominent tool in computational fluid dynamics , to cite but a few .

in recent two decades the lattice boltzmann method has been becoming a powerful tool for simulating complex systems .

deep neural networks have demonstrated stateof-the-art and sometimes human-competitive performance in numerous vision-related tasks .

convolutional neural networks , trained on large scale data , have significantly advanced the state-of-theart on traditional vision problems such as object recognition .

for the iv dataset , we follow the standard evaluation criterion to use the average precision as the measure .

we use the standard mean intersection-over-union score as the evaluation metric for both datasets .

as the phase space for the 2-sphere consists of a point , the wavefunction in this formulation is trivial .

the phase space a consist of the solutions of eq .

thus conventional dcf trackers can perform at more than 100 fps , which is significant for real-time applications .

conventional dcf trackers such as mosse , csk and kcf can perform at more than 100 fps .

since interval-valued fuzzy sets are widely studied and used , we describe briefly the work of gorzalczany on approximate reasoning .

since interval-valued fuzzy sets are widely studied and used , we describe briefly the work of gorzalczany on approximate reasoning in 1973 .

however , this structure will deteriorate the preamble detection performance over multipath channels .

in fact , a 0db echo channel with certain delay spread will entirely destroy the preamble detection .

we adopt a latency-oriented performance metric , called the normalized delivery time , introduced in .

we adopt the normalized delivery time , introduced in , as the performance metric of interest .

overlaid is the fit with an absorbed power law model described in the text .

overlaid is the exclusion result published in ref .

deep neural networks have shown great success in computer vision and natural language processing tasks .

deep neural networks show dramatically accurate results on challenging tasks .

the transverse gluon momentum characterizing the transition scale between the two regimes is called saturation momentum and is defined below .

the momentum qs at which this mechanism sets in is known as the saturation momentum .

sharing parameters between related tasks to improve joint performance is prominent in multitask learning .

in multitask learning , auxiliary data sets are harnessed to improve overall performance by exploiting regularities present across tasks .

advances in deep learning have led to tremendous success in a wide variety of applications in visual and audio perception such as image classification .

deep convolutional neural networks have achieved great success on many tasks across a variety of domains , such as vision .

thus we have proved the following theorem .

the converse direction is covered by the following theorem .

hydrogen is the main opacity source in the photospheres of o stars .

hydrogen is the chosen reference element since it is the most common element in the universe as a whole and that it normally dominates the continuous opacity in the formation of the stellar spectra .

the specific model to be 15 discussed here is the pair hidden markov model .

specific to our model is the explicit treatment of the mesonic degrees of freedom including retardation .

later , meeks and rosenberg generalized this result to complete , embedded minimal surfaces with positive injectivity radius in r 3 in .

after this , meeks and rosenberg proved that if σ is a complete embedded minimal surface in r 3 which has positive injectivity radius , then σ is proper , .

the functor dmb is an equivalence of triangulated monoidal categories .

this construction is compatible with composition of morphisms .

a qubit is a unit vector in the hilbert space c2 .

the qubit consists of the last two vectors .

the behavior of the color singlet free energy in the deconfined phase has been studied in coulomb gauge .

the color adjoint correlator in coulomb gauge has been studied in pure gauge theory .

generative adversarial networks have emerged as a powerful framework for learning generative models of arbitrarily complex data distributions .

generative adversarial networks have gained significant popularity in the machine learning community recently as it provides a novel and easy way to learn generative models .

these methods sometimes use multiple individual-tailored decisions to choose video portions for the summary and often rely on the determinantal point process in order to increase the diversity of selected video subsets .

these include method which use multiple man-tailored decisions to choose video portions for the summary and methods relying on the determinatal point process to increase the diversity of selected video subsets .

to speed up the sr process , dong et al extracted features directly from the lr image , that also achieved better performance compared to processing the upscaled lr image through bicubic interpolation .

to speed up the sr process , dong et al extracted features directly from the lr image , that also achieved better performance compared to processing the upscaled lr image through bicubic .

recently , cnns have been successfully applied to a variety of applications , including image classification .

cnns have been embraced across a wide array of fields , such as recommendation systems .

our proposed model is trained using the adam optimizer , with mini-batch size 30 .

we use the adam optimizer using a fixed batch size of 16 during training .

in particular , this property is inconsistent with a physical picture for parton branching at strong coupling .

in fact , the absence of the collinear singularity at strong coupling has been recurrently observed in the literature .

his recent research interests include cross layer design , interference management in interference network , and embedded system design .

his research interests include mimo communications with limited feedback , relay-assisted communications , and interference mitigation techniques .

we used the popular moses toolkit to train our smt system for the two language pairs .

we used the moses system as our baseline phrase-based smt system .

clearly the vacuum is a minimum of the potential in these directions , as confirmed , for all field directions , by a calculation of the eigenvalues of the mass matrix .

the vacuum is a dual superconductor in the confined phase and becomes trivial in the deconfined one .

by duality , there is a similar correspondence between right bol loops and right bol quasigroups .

duality is a deep concept in statistical mechanics and in quantum field theory .

in the past few years , convolutional neural networks have made tremendous progress in learning image features and solving various computer vision tasks .

for the past several years , deep convolution neural networks have found their extensive applications in image processing such as image classification , and so forth .

the data were calibrated in the common astronomy software application with the supplied calibration script .

the data were edited and calibrated following standard procedures within the common astronomy software application .

we consider a wireless network and we follow definitions given in .

we consider a wireless network model and we follow definitions given in .

in , socher et al proposed an unfolding recursive autoencoder for paraphrase identification .

socher et al present an approach based on recursive autoencoders for paraphrase detection .

deep convolutional neural networks have achieved great success in computer vision related tasks such as image classification , and so on .

convolutional neural networks have led to leap-forward in a large number of computer vision applications .

to accelerate convergence , we add batch normalization after each convolution and learn the scale and shift parameters during training .

after the training of each layer , we use batch normalization to avoid the internal covariate shift problem .

cosmic strings are effectively one-dimensional topological defects which may form at a phase transition in the early universe .

cosmic strings are a special kind of topological defects , which could have been formed in a symmetry breaking phase transition in the early universe .

however , one of the pilot agents failed to orre tly pro ess the mission statement .

however , due to an unexpe ted sensor failure , one of the atta kers failed to sense the way-point .

otherwise , the orbit contains only one element and is called a fixed orbit .

if the orbit is a horseshoe where the inner part has negative and the outer part positive sense of rotation , the soliton is unstable and desintegrates very quickly .

volatility is a measure of the uncertainty of price movements and is the standard way to characterize risk .

in the financial context , this observable is called volatility .

two of the most commonly used and efficient approaches are vae and generative adversarial networks .

variational autoencoders and generative adversarial networks have emerged as two of the most effective frameworks .

we compare the proposed method with 10 recent state-ofthe-art methods on aforementioned datasets , which include gmr .

finally , we compare our rds network with other state-of-the-art methods on five public sod datasets , hku-is .

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

deep neural networks have made great strides in many computer vision tasks such as image classification .

kim et al increased the network depth in vdsr by using gradient clipping , skip connection , or recursive-supervision to ease the difficulty of training deep network .

then , the drcn kim et al proposed relieved the difficulty of deep network training by using gradient clips , skipping connections and recursive supervision .

each activation layer is preceded by a layer of batch normalization .

the first four layers are followed by a batch normalization activation function .

standard multi-task learning aims at learning multiple tasks in a joint manner .

hence , multi-task learning employs sharing of fundamental knowledge across tasks .

this explains the strong anisotropy of the magnitude of the effect around the fermi surface .

the high energy dispersion does not extrapolate to the fermi surface crossing .

the immersed boundary method is a flexible approach for the treatment of moving boundaries with complex geometry .

the immersed boundary method is a very popular numerical approach in the simulation of complex and moving boundary problems .

it should be plausible that this is the case , at least if we exclude a finite number of values of the floquet exponents .

it is very plausible that this is the case .

deep feedforward neural networks , with multiple hidden layers , have achieved remarkable performance across many domains .

deep neural networks have been evolved to powerful predictive models with remarkable performance on computer vision tasks .

the connection to topological interference management problems follows from .

when the channel coefficients are fixed the topological interference management problem is shown in .

the approach thus needs only two database scans .

this approach needs only one pass of the database .

dropout is one of the most effective and widely used regularization techniques for neural networks .

dropconnect , is the method used for regularizing deep neural networks .

exchange-correlation energies are taken into account by the generalized gradient approximation using perdew-burke-ernzerhof functional .

the exchange-correlation functional is modeled in the generalized gradient approximation with the perdew-burke-ernzerhof realization .

deep networks have been successfully applied in various computer vision tasks , including image classification .

deep convolutional neural networks have been successful in many computer vision tasks including image classification .

deep convolutional neural networks have performed impressively on very large-scale image recognition problems .

deep convolutional neural networks have made significant breakthroughs in many visual understanding tasks including image classification .

the other known general criteria for subnormality , require the operator in question to have an invariant domain .

the other known criteria for subnormality require the operator in question to have an invariant domain .

zhu et al proposed a lstm network with a mixed-norm regularization term to cost functions in order to learn the co-occurrence of discriminative features from skeletal data .

zhu et al proposed a deep lstm network to model the inherent correlations among skeleton joints and the temporal dynamics in various actions .

gatenby and vincent adopted a game theory approach influenced by population dynamics to study tumour-host interactions in colorectal carcinogenesis .

gatenby and vincent adopted a game theory model heavily influenced by population dynamics to investigate the influence of the tumour-host interface in colorectal carcinogenesis .

introduction the longstanding problem of the generation of turbulence in various hydrodynamically stable situations has found a solution in recent years with the mhd shear flow instability , also called magnetorotational instability .

the other instability is the landau instability , which is applicable to the case with dissipation .

nt a dipolar condensate is a condensate possessing the dipole-dipole interactions , in addition to the usual swave contact interaction .

the pancake dipolar condensate is the first example of a weakly interacting gas , where the spectrum has a roton-maxon form .

convolutional neural networks have shown significant success in challenging tasks in image classification and recognition .

convolutional neural networks have achieved impressive state-of-the-art results on image classification .

gravity is a weak interaction , even at the enormous energies usually conceived for inflation , so the increment from each new pair is minuscule .

since gravity is a purely attractive force , and since the fluctuations on scales of the cmb anisotropies were small in amplitude when the anisotropies were generated , the fluctuations had to have been very small in the early universe .

these include the mutual coherence and the restricted isometry constants .

these include the mutual coherence and restricted isometery property .

the simplest of these constructions is the protocol for a secure hadamard gate .

in all of these constructions , the result is a seiberg-witten floer homology that can be shown to be of the form advertised above .

for the gmu component , we use batch normalization applied to each modality matrix .

for regularization purposes we have included dropout and batch normalization in each residual block .

possible-world semantics for autoepistemic logic .

a semantical approach to nonmonotonic logics .

in the past decade , grids have evolved as the infrastructure for delivering high-performance services for compute and data-intensive scientific applications .

in the past decade , grids have evolved as the infrastructure for delivering high-performance service for compute and data-intensive scientific applications .

the recent papers on compressive sensing provide the missing theoretical guarantees -conditions for exact recovery and error bounds when exact recovery is not possible .

the papers on compressive sensing from 2005 provide the missing theoretical guarantees -conditions for exact recovery and error bounds when exact recovery is not possible .

deep neural networks play an increasingly central role in a wide variety of state of the art machine learning applications .

in recent years , deep learning has emerged as the dominant solution showing remarkable success in a wide spectrum of artificial intelligence applications .

the lagrangian is the basis of our control theory , since it allows the derivation of the equations to be fulfilled by the control field .

the lagrangian for this is a natural generalisation of , with the addition of supersymmetry .

deep learning models have accomplished superior performance in several machine learning problems , which use either visual or audio sources .

convolutional neural networks have recently demonstrated impressive performance on various computer vision tasks such as semantic image segmentation and alike .

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

recently , deep neural networks have led to significant improvement in several machine learning domains , from speech recognition to computer vision and machine translation .

object detection with top-down segmentation feedback for the detection sub-network , we use the state-ofthe-art fastr-cnn .

we compare craft with state-of-the-art detectors under the two-step detection framework , which are fast r-cnn .

recognizability of graph and pattern languages .

finite-state recognizability of graph properties .

the spectra were fitted in xspec with a powerlaw plus multiple gaussian model , including fits for both emission lines and absorption lines .

the spectra were fitted in xspec with the mekal plasma emission code , absorbed by the phabs photoelectric absorption code .

in the monte carlo language this is known as thermalization .

per forming the monte carlo iterations to obtain such independent field configurations is called thermalization .