HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
convolutional neural network based models led to a series of breakthroughs in high-level computer vision tasks , such as image classification .	deep neural networks have shown state-of-the-art performance on many computer vision problems , including semantic segmentation .
convolutional neural networks have achieved exceptional results in many large-scale computer vision applications , particularly in image recognition task .	convolutional neural networks have led to leap-forward in a large number of computer vision applications .
the two most common and efficient generative approaches are variational autoencoders and generative adversarial networks .	the most popular generative model approaches are generative adversarial networks , variational autoencoders .
these show that the simulation is sensitive to the parameter infect rate .	these show that the simulation is not sensitive to the parameter cell lifespan .
where the tilde denotes the laplace transform .	a tilde will now denote bulk quantities , as opposed to brane quantities which carry a hat .
one laser is a unidirectional ring cavity , and the other laser is based on a σ-cavity design with a cavity mirror mounted on a piezoelectric transducer for low-bandwidth repetition-rate locking with the other laser .	the laser at 397nm is a frequency-doubled grating-stabilized diode laser .
we use the pytorch 1 framework for our implementation .	we use the pytorch library to train our local descriptor network .
polar codes , proposed by arikan , are low-complexity capacity-achieving codes based on the phenomenon called channel polarization .	polar codes are capacity-achieving error correcting codes , characterized by a low-complexity encoding and decoding process .
similar to u-net , we use skip connections between the feature encoder and the decoder .	additionally , we add skip connections from encoder layers to decoder layers , akin to the u-net architecture .
thus , deep learning has been broadly adapted to automotive systems .	indeed , deep learning has been adopted by many industries like car manufacturing .
deep neural networks have led to a revolution in the areas of machine learning , audio analysis , and computer vision , achieving state-of-the-art results in numerous applications .	recently , deep neural networks have gained the attention of numerous researchers outperforming state-of-the-art approaches on various computer vision tasks .
deep neural networks have significantly improved the performance of diverse data mining and computer vision applications .	deep convolutional neural networks have made great progress in visual recognition challenges such as object classification .
the spectra and dynamics of diatomic molecules .	dynamical properties of dipolar fermi gases .
millimeter wave communication is deemed as a promising technique for meeting the ever-increasing traffic demand in next generation wireless communication systems .	hyper-dense small cell networks have been recognized as a promising technology to achieve higher network capacity in fifth-generation wireless networks .
slivova for the ceres collaboration , this proceedings .	esumi for the phenix collaboration , this proceedings .
we extract the activations of the 5 th convolutional layer of the pre-trained vgg-16 network .	we extract feature maps as the intermediate activations of a pre-trained vgg-19 network .
lda assumes that there are topics in a document and words can be assigned to the topics with different weights .	lda assumes that documents contain latent topics and each topic can be represented by a distribution across words .
today the theory of narrow operators is a growing and active field of functional analysis .	today the theory of narrow operators is an active area of functional analysis .
however , these two maps are not transversal .	those two kinds of the boundary marked points are not symmetric .
if the social network is a single line graph with s0 being the two endpoints , the maximum expected revenue is at most a constant l .	social network is a graph derived from friendship relations on an online social network site .
deep neural networks are at the core of state-of-the-art models for supervised tasks like image recognition and speech recognition .	deep convolutional neural networks have achieved huge success in solving problems related to computer vision , such as image classification .
the spire data are reduced using a combination of the hipe and smap packages .	the data were reduced using the standard steps in miriad .
privacy preserving approaches have been studied for social networks , auditing queries , network routing .	privacy preserving approaches have been studied for social networks and in other contexts .
alur et al showed that the existence of robust control for the schedulability problem for bounded-rate multi-mode systems is , although intractable , decidable .	it is known that the schedulability and reachability problems for bounded-rate multi-mode systems are , although intractable , decidable .
is called a cartan decomposition of g and the procedure is known as the weyl unitary trick .	the trick is a bivariant generalization of the connes-moscovici method for finitely summable k-cycles .
optical production of ultracold polar molecules .	optical methods for indirect production of ultracold molecules .
the same guiding principles are applied to derive the convolutional factorization based on the euclidean distance in .	the exact same principles are applied in to derive a convolutional nmf based on the squared euclidean distance .
recently , deterministic deep neural networks have demonstrated state-of-the-art performance on many supervised tasks , eg , speech recognition .	in recent years , convolutional neural networks have achieved significant success in many computer vision tasks , including the super-resolution problem .
in this work , a convolutional layer is by default followed by batch normalization activation unit .	after every convolutional layer , batch normalization are applied to the output .
the input to the dual encoder is the logarithm of soft symbol estimates of the coded symbols obtained from the received signals , and the dual encoder output produces the logarithm of the soft symbol estimates of the information symbols .	with logarithm of the soft coded symbol estimate , directly obtained from the received signals , as the input to the dual encoder , the dual encoder output produces the logarithm of the soft symbol estimates of the binary information symbols .
deep neural networks have been extensively applied in many fields , such as image recognition .	convolutional neural networks has shown phenomenal results for many computer vision applications .
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 .	in the milky way there is the sagittarius dwarf galaxy , which is currently being sheared apart through gravitational interaction with our galaxy .
low-density parity-check codes were first introduced by gallager in 1990s .	low-density parity-check block codes were first invented by gallager .
zia , in phase transitions and critical phenomena , edited by c .	mukamel , in soft and fragile matter , edited by m .
in recent years , convolutional neural networks has achieved remarkable results in a wide range of computer vision applications .	in recent years , deep neural networks have led to many breakthrough results in machine learning and computer vision , and are now widely deployed in industry .
the perdew-burkeernzerhof generalized-gradient approximation is employed to describe the exchange and correlation functional .	the exchangecorrelation energy functional is described with the spin-polarized generalized gradient approximation as parameterized by perdew-burke-ernzerhof .
owing to recent advances in nanotechnology , plasmonic nanoantennas have become a subject of considerable theoretical and experimental interest .	plasmonic nanoantennas have become a subject of considerable theoretical and experimental interest .
the muon decay is a little more involved , since the final state involves two neutrinos , where one of these is not observed .	muon decay is a three-body decay , so the 3 1 gev muons produce a continuum of positrons from the end-point energy down .
we use the commonly accepted external memory model by aggarwal and vitter .	we consider the commonly accepted external-memory model by aggarwal and vitter .
if the higgs boson is a very narrow resonance , we will observe a rapid increase in the visible cross section of the higgs production during energy scanning .	this massive spin-0 particle is known as the higgs boson .
we employed several different exchange-correlation functionals , namely pbe for gete models .	we used both the generalized-gradientapproximation to model exchange-correlation effects .
for each of the proteins studied , there is a broad plateau of optimal folding .	these proteins are defined as integral or intrinsic .
we provide brief introduction about the idea of mean embedding of distributions into rkhs and the metric of mmd .	we provide a brief introduction of the idea on mean embedding of distributions into rkhs and the metric of mmd .
the data were calibrated and flagged for rfi using the nrao casa pipeline .	the data were processed through the vla casa calibration pipeline .
in terms of partitions , σt is the sum of all three block partitions such that the second block is empty .	in terms of partitions , σ1 is the sum of all three block partitions such that the central block is empty .
deep convolutional neural networks have emerged as highly effective models for these large-scale visual recognition tasks .	deep convolutional neural networks have made significant progress in classification problems , which have shown to generate good results when provided sufficient data .
the top panel shows the power spectrum produced from the difference of maps made with left and right going chopper sweeps .	the central panel shows the power spectrum produced from the difference of maps made with values of azimuth toward and away from the mapo building .
cluster algebras were introduced by fomin and zelevinsky in in order to study total positivity and canonical bases in semisimple groups .	cluster algebras were introduced by fomin and zelevinsky with the aim to set up a combinatorial framework for the study of total positivity in algebraic groups and canonical bases in quantum groups .
hinton et al used unsupervised learning to obtain an initial configuration of the parameters .	hinton et al introduced a learning algorithm that utilizes layerwise unsupervised pre-training to initialize all layers .
deep neural networks have achieved a great success on many tasks such as image classification when a large set of labeled examples are available .	convolutional neural networks have achieved superior performance in many visual tasks , such as object classification and detection .
the diagrammatic representation of a summand in such a perturbation series is called a feynman diagram .	feynman diagram is the most familiar graph method to represent a scattering amplitude .
quantum teleportation is a conceptually remarkable phenomenon .	quantum teleportation is a universal computa tional primitive .
millimeter wave communications is a promising candidate technology for the next generation of wireless networks .	large mimo is believed to be one of the key technologies for 5g wireless systems .
we also show the gravitational-wave signal-to-noise ratios resulting from the glitch model discussed in the main text .	we also indicate the effective gravitational-wave amplitudes from the glitch-induced mode-oscillations discussed in the text .
the integration over negative particle energies will be associated with positive energy .	the intermediate state in the amplitude will be integrated over all energies for the particles .
recent works use deep neural networks and large supervised training sets .	recently , methods employing cnn based learning approaches led to important progress .
it is easily verified sp is an infinite special interval semiring .	clearly sg is an infinite commutative interval group semiring .
furthermore , the mechanism of the m-ary fsk signal detection via short time sr effects is explicated in terms of the receiver response speed .	in view of the receiver response speed , the mechanism of the m-ary fsk signal detection is explained .
molecular motors are protein complexes of the size of nanometers that convert chemical energy into mechanical motion .	motor proteins are nano-machines that convert chemical energy into mechanical work and motion .
neural machine translation has recently become the stateof-the-art approach to machine translation .	neural machine translation has recently become the state-of-the-art approach to machine translation .
dft calculations were performed using the projector augmented wave function method implemented in the gpaw code within the local density approximation 38 for the exchange and correlation -functional .	the dft calculations were performed using the pbe exchange-correlation functional , the projector augmented wave method 39 , and a real space grid for the expansion of the wave functions , as implemented in the gpaw code 40 .
recently , convolutional neural networks -based methods achieve great success in image classification tasks .	recently , deep convolutional neural networks have attracted a lot of attention in visual recognition due to its good performance .
the encoder is composed of residual blocks based on the resnet-50 architecture .	the pix2vex architecture is based on a pix2pix convolutional and deconvolutional resnet network .
he et al use the residual learning framework to ease the training of networks .	he et al eased the training of a 152 layers deep cnn by presenting a residual learning framework .
let us notice that an ornstein-uhlenbeck process is the sum of a damping term and an excitation term .	a solution of this equation is called an ornstein-uhlenbeck process .
we use adam as the optimizer to perform stochastic gradient ascent .	we use adam to minimize the objective function , which usually can converge within 20 epochs .
the compactness is a consequence of the following eg theorem .	now , compactness is the crucial element in the proof of a maximizing continuum .
conventional hrrsir methods are mainly based on low-level feature representations , such as global features including spectral features , which can achieve satisfactory performance to some extent .	traditional hrrsir methods are mainly based on low-level feature representations , such as global features including spectral features , which can achieve satisfactory performance to some extent .
zwiebach , classical solutions in string field theory around the tachyon vacuum , adv .	zwiebach , string field theory around the tachyon vacuum , adv .
since the higgs field is a component of the four-dimensional gluon field , no linear divergence of the higgs self-energy can occur due to the slavnov-taylor identities of the four-dimensional theory .	while the higgs is a component of the vector multiplet in the bulk , as far as these fixed points are concerned they are components of matter type multiplets , and the restricted symmetries may allow independent yukawa interactions to be located on these fixed points .
chen et al employed lstm to capture long-distance preceding context .	chen et al used a long shortterm memory network to capture long-distance context .
lin and hauptmann proposed a simple approach based on using colour features in a time-constrained k-means clustering algorithm , capable of maintaining temporal coherence on the splitting of events .	lin and hauptmann also propose a simple approach based on using colour features in a time-constrained k-means clustering algorithm for keeping temporal coherence .
for svm , we use the liblinear library that provides a highly efficient implementation of the linear svm for parallel execution on cpus .	more specifically , the implementation we choose is the linearsvc class based on the liblinear library .
a meson is a quark-antiquark bound state which corresponds to a pole in the series .	we also know that meson is a ompli ated solution of the qcd quark and gluon elds that involve a real quark-antiquark pair .
wz sge is a very famous , bright variable star now known to be the closest cataclysmic variable .	wz sge is the only eclipsing system among the known wz sge stars .
this fact was first established in by using the equivalence of and and showing that does not hold .	this fact was established in via the equivalence of and and showing that does not hold .
it was also proven in that the problems that arise from ne when one restricts the search space to equilibria in positional or stationary strategies are both np-hard .	in particular , it was shown in that ne becomes undecidable if one restricts the search space to equilibria in pure strategies , even for simple stochastic multiplayer games .
sandia is a multipurpose 17 laboratory operated by sandia corporation , a lockheed-martin company , for the united states department of energy under contract de-ac04-94al85000 .	sandia is a multiprogram laboratory operated by sandia corporation , a lockheed martin company , for the united states department of energy under contract de-ac04-94al85000 1 s .
this is in contrast to the work of carlip and vaidya , where the latter choice for boundary term k 0 was chosen , so that the action vanishes for flat space .	this makes empty de sitter space the reference point for the energy , in contrast to the work of carlip and vaidya , where the boundary term is chosen so that the action vanishes for flat spacetime .
as mentioned , the key insight dates back to a 1978 paper of sakoda and sipser .	this approach was suggested in the original paper by sakoda and sipser .
in the d-rls algorithm , we use the laplacian combination rule for the incremental update and the metropolis combination rule for the spatial update .	here , we consider the diffusion recursive least squares algorithm for the incremental update and relativevariance combination rule for the spatial update .
we compare our proposed salient object detector with 16 recent state-of-the-art saliency models , including drfi 0 table 3 .	we exhaustively compare our proposed approach with 12 existing state-of-the-art salient object detection methods including 2 classic methods and 10 recent cnn-based methods .
maybe string theory is the solution and we just have to understand it better or maybe we have to modify it in some way .	if string theory is the ultimate theory of nature then the proposal of add might be embedded within it with a bulk supporting a supersymmetric gravitational action , with supersymmetry serving as a mechanism for stabilizing the bulk radii .
quantization of the schlesinger system leads to some version of the knizhnik-zamolodchikov-bernard equations .	such a quantization of isomonodromic systems gives rise to the knizhnik-zamolodchikov-bernard equations .
deep convolutional neural networks have achieved remarkable accuracy for tasks in a wide range of application domains including image processing , machine translation , and speech recognition .	convolutional neural networks have recently provided state of the art results for several recognition tasks including object recognition .
schematic image of the disk and magnetization distribution .	schematic images of the domain in the magnetic disk and electric current .
recent advances on convolutional neural networks have achieved superior results and are currently replacing rdfs in most state-of-the-art methods .	multi-layer convolutional neural networks pioneered by lecun et al have led to breakthrough results , constituting the state-of-the art technology for many challenges such as imagenet .
somewhat orthogonally , a large body of work exists on randomly deployed wireless networks , starting with the influential work by gupta and kumar .	the seminal work of gupta and kumar on the capacity of wireless networks stimulated extensive studies covering a broad range of networking problems with different performance metrics .
the ellipses denote the o in the pion da .	as before , the ellipses denote non-quadratic powers of p .
szegedy et al first demonstrated that neural networks are vulnerable to adversarial examples .	for example , szegedy et al find that deep neural networks are easily fooled by adversarial examples .
filimonov , demos and sornette calibrated the lppls model by applying the modified profile likelihood inference method and obtained the interval estimation for the critical time .	filimonov , demos and sornette applied the modified profile likelihood inference method to calibrate the lppls model for financial bubbles and obtained the interval estimation for the critical time .
the first term with totally symmetric spin three index corresponds to the gauge artifact of the positive-norm spin four state , and the mixed symmetric tensor structure of the second term is exactly the same as that of the positive-norm spin three state .	with totally symmetric spin three index corresponds to the gauge artifact of the positive-norm spin four state , and the mixed symmetric tensor structure of the second term is exactly the same as that of the positive-norm spin three state .
the isoscalar parameters of these parameter sets can be seen in table ii .	the parameters of some exemplary test parameter sets can be seen in table i .
the wilson loop of the lax connection defines an infinite set of conserved charges , which include the global noether charges of the left group multiplication .	the monodromy matrix of the lax connection then generates an infinite set of local or non-local commuting conserved charges .
its peculiarity consists of an astonishing regularity of the geometric trajectory in phase space .	another peculiarity is the anomalously high admittance factors at the seshan25 and tsukub32 stations .
bourbonnais , in trends in high magnetic fields science , edited by l .	jacobsen , in low dimensional conductors and superconductors , edited by d .
the global optimisation here is not a decentralised super-peer based control mechanism , but the completely distributed peer-to-peer network of the interconnected habitats , and therefore not susceptible to super-peer failure .	the global optimisation here is not a decentralised super-peer based control mechanism , but the completely distributed peer-to-peer network of the interconnected habitats , which is not susceptible to the failure of super-peers .
pl measurements are performed with a homebuilt sample-scanning confocal microscopy system .	a homebuilt confocal microscopy system is used to perform pl measurements at room temperature .
generative adversarial networks are a recent popular technique for learning generative models for high-dimensional unstructured data .	generative adversarial networks are a recent neural network architecture that allow for very good generative models .
the perdew-burke-ernzerhof parametrization for the exchange-correlation functional has been used .	the generalized gradient approximation of perdew , burke and ernzerhof was employed for the exchange-correlation potential .

convolutional neural network based models led to a series of breakthroughs in high-level computer vision tasks , such as image classification .

deep neural networks have shown state-of-the-art performance on many computer vision problems , including semantic segmentation .

convolutional neural networks have achieved exceptional results in many large-scale computer vision applications , particularly in image recognition task .

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

the two most common and efficient generative approaches are variational autoencoders and generative adversarial networks .

the most popular generative model approaches are generative adversarial networks , variational autoencoders .

these show that the simulation is sensitive to the parameter infect rate .

these show that the simulation is not sensitive to the parameter cell lifespan .

where the tilde denotes the laplace transform .

a tilde will now denote bulk quantities , as opposed to brane quantities which carry a hat .

one laser is a unidirectional ring cavity , and the other laser is based on a σ-cavity design with a cavity mirror mounted on a piezoelectric transducer for low-bandwidth repetition-rate locking with the other laser .

the laser at 397nm is a frequency-doubled grating-stabilized diode laser .

we use the pytorch 1 framework for our implementation .

we use the pytorch library to train our local descriptor network .

polar codes , proposed by arikan , are low-complexity capacity-achieving codes based on the phenomenon called channel polarization .

polar codes are capacity-achieving error correcting codes , characterized by a low-complexity encoding and decoding process .

similar to u-net , we use skip connections between the feature encoder and the decoder .

additionally , we add skip connections from encoder layers to decoder layers , akin to the u-net architecture .

thus , deep learning has been broadly adapted to automotive systems .

indeed , deep learning has been adopted by many industries like car manufacturing .

deep neural networks have led to a revolution in the areas of machine learning , audio analysis , and computer vision , achieving state-of-the-art results in numerous applications .

recently , deep neural networks have gained the attention of numerous researchers outperforming state-of-the-art approaches on various computer vision tasks .

deep neural networks have significantly improved the performance of diverse data mining and computer vision applications .

deep convolutional neural networks have made great progress in visual recognition challenges such as object classification .

the spectra and dynamics of diatomic molecules .

dynamical properties of dipolar fermi gases .

millimeter wave communication is deemed as a promising technique for meeting the ever-increasing traffic demand in next generation wireless communication systems .

hyper-dense small cell networks have been recognized as a promising technology to achieve higher network capacity in fifth-generation wireless networks .

slivova for the ceres collaboration , this proceedings .

esumi for the phenix collaboration , this proceedings .

we extract the activations of the 5 th convolutional layer of the pre-trained vgg-16 network .

we extract feature maps as the intermediate activations of a pre-trained vgg-19 network .

lda assumes that there are topics in a document and words can be assigned to the topics with different weights .

lda assumes that documents contain latent topics and each topic can be represented by a distribution across words .

today the theory of narrow operators is a growing and active field of functional analysis .

today the theory of narrow operators is an active area of functional analysis .

however , these two maps are not transversal .

those two kinds of the boundary marked points are not symmetric .

if the social network is a single line graph with s0 being the two endpoints , the maximum expected revenue is at most a constant l .

social network is a graph derived from friendship relations on an online social network site .

deep neural networks are at the core of state-of-the-art models for supervised tasks like image recognition and speech recognition .

deep convolutional neural networks have achieved huge success in solving problems related to computer vision , such as image classification .

the spire data are reduced using a combination of the hipe and smap packages .

the data were reduced using the standard steps in miriad .

privacy preserving approaches have been studied for social networks , auditing queries , network routing .

privacy preserving approaches have been studied for social networks and in other contexts .

alur et al showed that the existence of robust control for the schedulability problem for bounded-rate multi-mode systems is , although intractable , decidable .

it is known that the schedulability and reachability problems for bounded-rate multi-mode systems are , although intractable , decidable .

is called a cartan decomposition of g and the procedure is known as the weyl unitary trick .

the trick is a bivariant generalization of the connes-moscovici method for finitely summable k-cycles .

optical production of ultracold polar molecules .

optical methods for indirect production of ultracold molecules .

the same guiding principles are applied to derive the convolutional factorization based on the euclidean distance in .

the exact same principles are applied in to derive a convolutional nmf based on the squared euclidean distance .

recently , deterministic deep neural networks have demonstrated state-of-the-art performance on many supervised tasks , eg , speech recognition .

in recent years , convolutional neural networks have achieved significant success in many computer vision tasks , including the super-resolution problem .

in this work , a convolutional layer is by default followed by batch normalization activation unit .

after every convolutional layer , batch normalization are applied to the output .

the input to the dual encoder is the logarithm of soft symbol estimates of the coded symbols obtained from the received signals , and the dual encoder output produces the logarithm of the soft symbol estimates of the information symbols .

with logarithm of the soft coded symbol estimate , directly obtained from the received signals , as the input to the dual encoder , the dual encoder output produces the logarithm of the soft symbol estimates of the binary information symbols .

deep neural networks have been extensively applied in many fields , such as image recognition .

convolutional neural networks has shown phenomenal results for many computer vision applications .

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 .

in the milky way there is the sagittarius dwarf galaxy , which is currently being sheared apart through gravitational interaction with our galaxy .

low-density parity-check codes were first introduced by gallager in 1990s .

low-density parity-check block codes were first invented by gallager .

zia , in phase transitions and critical phenomena , edited by c .

mukamel , in soft and fragile matter , edited by m .

in recent years , convolutional neural networks has achieved remarkable results in a wide range of computer vision applications .

in recent years , deep neural networks have led to many breakthrough results in machine learning and computer vision , and are now widely deployed in industry .

the perdew-burkeernzerhof generalized-gradient approximation is employed to describe the exchange and correlation functional .

the exchangecorrelation energy functional is described with the spin-polarized generalized gradient approximation as parameterized by perdew-burke-ernzerhof .

owing to recent advances in nanotechnology , plasmonic nanoantennas have become a subject of considerable theoretical and experimental interest .

plasmonic nanoantennas have become a subject of considerable theoretical and experimental interest .

the muon decay is a little more involved , since the final state involves two neutrinos , where one of these is not observed .

muon decay is a three-body decay , so the 3 1 gev muons produce a continuum of positrons from the end-point energy down .

we use the commonly accepted external memory model by aggarwal and vitter .

we consider the commonly accepted external-memory model by aggarwal and vitter .

if the higgs boson is a very narrow resonance , we will observe a rapid increase in the visible cross section of the higgs production during energy scanning .

this massive spin-0 particle is known as the higgs boson .

we employed several different exchange-correlation functionals , namely pbe for gete models .

we used both the generalized-gradientapproximation to model exchange-correlation effects .

for each of the proteins studied , there is a broad plateau of optimal folding .

these proteins are defined as integral or intrinsic .

we provide brief introduction about the idea of mean embedding of distributions into rkhs and the metric of mmd .

we provide a brief introduction of the idea on mean embedding of distributions into rkhs and the metric of mmd .

the data were calibrated and flagged for rfi using the nrao casa pipeline .

the data were processed through the vla casa calibration pipeline .

in terms of partitions , σt is the sum of all three block partitions such that the second block is empty .

in terms of partitions , σ1 is the sum of all three block partitions such that the central block is empty .

deep convolutional neural networks have emerged as highly effective models for these large-scale visual recognition tasks .

deep convolutional neural networks have made significant progress in classification problems , which have shown to generate good results when provided sufficient data .

the top panel shows the power spectrum produced from the difference of maps made with left and right going chopper sweeps .

the central panel shows the power spectrum produced from the difference of maps made with values of azimuth toward and away from the mapo building .

cluster algebras were introduced by fomin and zelevinsky in in order to study total positivity and canonical bases in semisimple groups .

cluster algebras were introduced by fomin and zelevinsky with the aim to set up a combinatorial framework for the study of total positivity in algebraic groups and canonical bases in quantum groups .

hinton et al used unsupervised learning to obtain an initial configuration of the parameters .

hinton et al introduced a learning algorithm that utilizes layerwise unsupervised pre-training to initialize all layers .

deep neural networks have achieved a great success on many tasks such as image classification when a large set of labeled examples are available .

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

the diagrammatic representation of a summand in such a perturbation series is called a feynman diagram .

feynman diagram is the most familiar graph method to represent a scattering amplitude .

quantum teleportation is a conceptually remarkable phenomenon .

quantum teleportation is a universal computa tional primitive .

millimeter wave communications is a promising candidate technology for the next generation of wireless networks .

large mimo is believed to be one of the key technologies for 5g wireless systems .

we also show the gravitational-wave signal-to-noise ratios resulting from the glitch model discussed in the main text .

we also indicate the effective gravitational-wave amplitudes from the glitch-induced mode-oscillations discussed in the text .

the integration over negative particle energies will be associated with positive energy .

the intermediate state in the amplitude will be integrated over all energies for the particles .

recent works use deep neural networks and large supervised training sets .

recently , methods employing cnn based learning approaches led to important progress .

it is easily verified sp is an infinite special interval semiring .

clearly sg is an infinite commutative interval group semiring .

furthermore , the mechanism of the m-ary fsk signal detection via short time sr effects is explicated in terms of the receiver response speed .

in view of the receiver response speed , the mechanism of the m-ary fsk signal detection is explained .

molecular motors are protein complexes of the size of nanometers that convert chemical energy into mechanical motion .

motor proteins are nano-machines that convert chemical energy into mechanical work and motion .

neural machine translation has recently become the stateof-the-art approach to machine translation .

neural machine translation has recently become the state-of-the-art approach to machine translation .

dft calculations were performed using the projector augmented wave function method implemented in the gpaw code within the local density approximation 38 for the exchange and correlation -functional .

the dft calculations were performed using the pbe exchange-correlation functional , the projector augmented wave method 39 , and a real space grid for the expansion of the wave functions , as implemented in the gpaw code 40 .

recently , convolutional neural networks -based methods achieve great success in image classification tasks .

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

the encoder is composed of residual blocks based on the resnet-50 architecture .

the pix2vex architecture is based on a pix2pix convolutional and deconvolutional resnet network .

he et al use the residual learning framework to ease the training of networks .

he et al eased the training of a 152 layers deep cnn by presenting a residual learning framework .

let us notice that an ornstein-uhlenbeck process is the sum of a damping term and an excitation term .

a solution of this equation is called an ornstein-uhlenbeck process .

we use adam as the optimizer to perform stochastic gradient ascent .

we use adam to minimize the objective function , which usually can converge within 20 epochs .

the compactness is a consequence of the following eg theorem .

now , compactness is the crucial element in the proof of a maximizing continuum .

conventional hrrsir methods are mainly based on low-level feature representations , such as global features including spectral features , which can achieve satisfactory performance to some extent .

traditional hrrsir methods are mainly based on low-level feature representations , such as global features including spectral features , which can achieve satisfactory performance to some extent .

zwiebach , classical solutions in string field theory around the tachyon vacuum , adv .

zwiebach , string field theory around the tachyon vacuum , adv .

since the higgs field is a component of the four-dimensional gluon field , no linear divergence of the higgs self-energy can occur due to the slavnov-taylor identities of the four-dimensional theory .

while the higgs is a component of the vector multiplet in the bulk , as far as these fixed points are concerned they are components of matter type multiplets , and the restricted symmetries may allow independent yukawa interactions to be located on these fixed points .

chen et al employed lstm to capture long-distance preceding context .

chen et al used a long shortterm memory network to capture long-distance context .

lin and hauptmann proposed a simple approach based on using colour features in a time-constrained k-means clustering algorithm , capable of maintaining temporal coherence on the splitting of events .

lin and hauptmann also propose a simple approach based on using colour features in a time-constrained k-means clustering algorithm for keeping temporal coherence .

for svm , we use the liblinear library that provides a highly efficient implementation of the linear svm for parallel execution on cpus .

more specifically , the implementation we choose is the linearsvc class based on the liblinear library .

a meson is a quark-antiquark bound state which corresponds to a pole in the series .

we also know that meson is a ompli ated solution of the qcd quark and gluon elds that involve a real quark-antiquark pair .

wz sge is a very famous , bright variable star now known to be the closest cataclysmic variable .

wz sge is the only eclipsing system among the known wz sge stars .

this fact was first established in by using the equivalence of and and showing that does not hold .

this fact was established in via the equivalence of and and showing that does not hold .

it was also proven in that the problems that arise from ne when one restricts the search space to equilibria in positional or stationary strategies are both np-hard .

in particular , it was shown in that ne becomes undecidable if one restricts the search space to equilibria in pure strategies , even for simple stochastic multiplayer games .

sandia is a multipurpose 17 laboratory operated by sandia corporation , a lockheed-martin company , for the united states department of energy under contract de-ac04-94al85000 .

sandia is a multiprogram laboratory operated by sandia corporation , a lockheed martin company , for the united states department of energy under contract de-ac04-94al85000 1 s .

this is in contrast to the work of carlip and vaidya , where the latter choice for boundary term k 0 was chosen , so that the action vanishes for flat space .

this makes empty de sitter space the reference point for the energy , in contrast to the work of carlip and vaidya , where the boundary term is chosen so that the action vanishes for flat spacetime .

as mentioned , the key insight dates back to a 1978 paper of sakoda and sipser .

this approach was suggested in the original paper by sakoda and sipser .

in the d-rls algorithm , we use the laplacian combination rule for the incremental update and the metropolis combination rule for the spatial update .

here , we consider the diffusion recursive least squares algorithm for the incremental update and relativevariance combination rule for the spatial update .

we compare our proposed salient object detector with 16 recent state-of-the-art saliency models , including drfi 0 table 3 .

we exhaustively compare our proposed approach with 12 existing state-of-the-art salient object detection methods including 2 classic methods and 10 recent cnn-based methods .

maybe string theory is the solution and we just have to understand it better or maybe we have to modify it in some way .

if string theory is the ultimate theory of nature then the proposal of add might be embedded within it with a bulk supporting a supersymmetric gravitational action , with supersymmetry serving as a mechanism for stabilizing the bulk radii .

quantization of the schlesinger system leads to some version of the knizhnik-zamolodchikov-bernard equations .

such a quantization of isomonodromic systems gives rise to the knizhnik-zamolodchikov-bernard equations .

deep convolutional neural networks have achieved remarkable accuracy for tasks in a wide range of application domains including image processing , machine translation , and speech recognition .

convolutional neural networks have recently provided state of the art results for several recognition tasks including object recognition .

schematic image of the disk and magnetization distribution .

schematic images of the domain in the magnetic disk and electric current .

recent advances on convolutional neural networks have achieved superior results and are currently replacing rdfs in most state-of-the-art methods .

multi-layer convolutional neural networks pioneered by lecun et al have led to breakthrough results , constituting the state-of-the art technology for many challenges such as imagenet .

somewhat orthogonally , a large body of work exists on randomly deployed wireless networks , starting with the influential work by gupta and kumar .

the seminal work of gupta and kumar on the capacity of wireless networks stimulated extensive studies covering a broad range of networking problems with different performance metrics .

the ellipses denote the o in the pion da .

as before , the ellipses denote non-quadratic powers of p .

szegedy et al first demonstrated that neural networks are vulnerable to adversarial examples .

for example , szegedy et al find that deep neural networks are easily fooled by adversarial examples .

filimonov , demos and sornette calibrated the lppls model by applying the modified profile likelihood inference method and obtained the interval estimation for the critical time .

filimonov , demos and sornette applied the modified profile likelihood inference method to calibrate the lppls model for financial bubbles and obtained the interval estimation for the critical time .

the first term with totally symmetric spin three index corresponds to the gauge artifact of the positive-norm spin four state , and the mixed symmetric tensor structure of the second term is exactly the same as that of the positive-norm spin three state .

with totally symmetric spin three index corresponds to the gauge artifact of the positive-norm spin four state , and the mixed symmetric tensor structure of the second term is exactly the same as that of the positive-norm spin three state .

the isoscalar parameters of these parameter sets can be seen in table ii .

the parameters of some exemplary test parameter sets can be seen in table i .

the wilson loop of the lax connection defines an infinite set of conserved charges , which include the global noether charges of the left group multiplication .

the monodromy matrix of the lax connection then generates an infinite set of local or non-local commuting conserved charges .

its peculiarity consists of an astonishing regularity of the geometric trajectory in phase space .

another peculiarity is the anomalously high admittance factors at the seshan25 and tsukub32 stations .

bourbonnais , in trends in high magnetic fields science , edited by l .

jacobsen , in low dimensional conductors and superconductors , edited by d .

the global optimisation here is not a decentralised super-peer based control mechanism , but the completely distributed peer-to-peer network of the interconnected habitats , and therefore not susceptible to super-peer failure .

the global optimisation here is not a decentralised super-peer based control mechanism , but the completely distributed peer-to-peer network of the interconnected habitats , which is not susceptible to the failure of super-peers .

pl measurements are performed with a homebuilt sample-scanning confocal microscopy system .

a homebuilt confocal microscopy system is used to perform pl measurements at room temperature .

generative adversarial networks are a recent popular technique for learning generative models for high-dimensional unstructured data .

generative adversarial networks are a recent neural network architecture that allow for very good generative models .

the perdew-burke-ernzerhof parametrization for the exchange-correlation functional has been used .

the generalized gradient approximation of perdew , burke and ernzerhof was employed for the exchange-correlation potential .