HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
it plays an important role in various fields such as the thermodynamics and so on .	it is an important aspect in many research fields such as low-temperature thermodynamics .
deep feedforward neural networks , with multiple hidden layers , have achieved remarkable performance across many domains .	with the development of machine learning technologies , deep neural networks have shown their extraordinary performance for their high accuracy and excellent scalability .
the ordinate is the phase with 0 0 value corresponding to the deeper eclipse .	the ordinate is the flux normalized to the maximum .
huisken-ilmanen extended the imcf using geometric measure theory to prove the penrose conjecture .	huisken-ilmanen used imcf in the asymptotically flat manifolds to prove the penrose inequality .
we initialize the parameters in the convolutional and fully connected layers by following the proposed scheme in glorot and bengio .	all trainable parameters in our model are initialized by the method described by glorot and bengio .
deep convolutional neural networks achieve impressive performance on many computer vision tasks , including image classification .	deep neural networks have demonstrated significant performance improvements in a wide range of computer vision tasks .
generative adversarial nets are widely applied in generative models and have outstanding performance .	generative models , eg , variational auto-encoder , generative adversarial networks , provide a promising solution to this problem .
quantum computation is a catch-all for several models of computation based on a theoretical ability to manufacture , manipulate and measure quantum states .	quantum computation consists of single-qubit measurements on the graph states and every quantum algorithm is encoded in a measurement blueprint .
at the same time our simulation show that the structural phase transition will lead to the saturation of the number of alloying au atoms .	furthermore , our simulation shows that the structural phase transition will lead to the saturation of the number of alloying au atoms .
the approximation developed is based on the concept of decoding cells introduced in .	the approximation is based on the concept of decoding cells introduced in .
we also find that effective susy breaking scale observed on our wall becomes exponentially small as the distance between two walls grows .	we also find that effective susy breaking scale becomes exponentially small as the distance between two walls grows .
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 .	neural network learning has become a key practical machine learning approach and has achieved remarkable success in a wide range of real-world domains , such as computer vision , speech recognition , and game playing .
deep neural networks achieve near-human accuracy on many perception tasks .	deep neural networks play important roles in various computer vision tasks , eg , depth estimation .
for a k-algebra a , we denote by mod a the category of right a-modules , and denote by proj a for the induced derived functor .	let a be an affine hopf k-algebra which is a finite module over its center .
in section 2 we recall fundamental facts about g-covering functors from .	in section 3 we recall the definition and characterizations of orbit category from .
the communication capacity between job processes of a round-robin cpu scheduler was studied in .	a covert channel between two job processes sharing a round robin scheduler was studied in .
when b is a dense dcl-independent subset of a , the pair has elimination of imaginaries by .	again , note that when b is a dense dcl-independent subset of a , the pair has elimination of imaginaries by .
deep convolutional neural networks have achieved state-of-the-art performance on several image processing and computer vision tasks like image classification , object detection , and segmentation .	deep convolutional neural networks have rapidly matured as an effective tool for almost all computer vision tasks , including object recognition , classification , segmentation , superresolution , etc .
approximation algorithms for concave cost network flow problems .	solution methods for nonconvex network flow problems .
chen et al proposed gated recursive neural network to model feature combinations of context characters .	chen et al proposed gated recursive neural networks to model feature combinations .
currently , we claim this relation as a conjecture , however , we expect that a complete proof could be obtained by a rather straightforward generalization of the results of , devoted to discrete-spin models connected with the slalgebra .	we expect that a complete proof could be obtained by a rather straightforward generalization of the results of , devoted to discrete-spin models connected with the slalgebra .
the electron-ion interaction is described by the projected augmented wave potentials .	the exchange and correlation effect among electrons is described with the generalized gradient approximation .
for exchange and correlation the localdensity approximation , parametrized by perdew , burke and ernzerhof , was used .	the exchange and correlation energies were considered in the generalized gradient approximation following the perdew-burkeernzerhof parametrization scheme .
a monoid is a commutative semi-group with a unit .	an associative polyadic system with identity is called a polyadic monoid .
the entropy dissipation can be bounded from below by the relative entropy by means of the convex sobolev inequality .	a convex sobolev inequality with the auxiliary functional as its relative fisher information finally yields the exponential decay of the relative entropy .
deep neural networks have been widely applied in various fields , including computer vision he et al , among many others .	since 2012 , neural networks and deep architectures have proven very effective in application areas such as computer vision .
one of the most natural extensions of the standard model of particle physics is supersymmetry .	supersymmetry is generally regarded as one of the likely extensions to the standard model of particle physics .
tem micrograph of hgte nanoparticles , inset the diffraction pattern .	tem micrograph of hgte - ssdna complex nanostars , inset the diffraction pattern .
since the deuteron is the simplest nucleus containing a neutron , the process of pion production on the deuteron can be used for examining pion production on a neutron .	indeed , because the deuteron is a loosely bound system , one might expect to learn a host of spin-dependent properties of the neutron and proton as free particles .
this explains the close relation between the abjm theory and the theory for d-branes on the conifold .	this gives the theory of that lives 1 on n d3-branes sitting at the conifold singularity of a calabi-yau three-fold .
there was no steady input of energy and no obvious dissipation .	again there was no steady input of energy and no obvious dissipation .
this research has made use of the simbad database , operated at cds , strasbourg , france .	this work has made use of services produced by the michelson science center at the california institute of technology .
since the 1d profile is a reasonable proxy for the 3d profiles , the transmission spectra look very similar .	a profile is a finite list of linear orders on the alternatives which represent the individual choices .
however , it is shown in that this assumption is reasonable for parameter estimation over sparse binary matrices .	however , it is shown in that this assumption is reasonable for parameter estimation over ldpc codes .
reddit is a news aggregation website and online social platform launched in 2005 by steve huffman and alexis ohanian .	reddit is a news aggregation website and online social platform , which was launched in 2005 by steve huffman and alexis ohanian .
the number of collaboration in science has been steadily increasing for decades .	the characteristic collaboration size in science has been steadily increasing over the last century .
it has been convincingly argued that the physical origin of these singularities is either a set of gauge bosons becoming massless or an entire string becoming tensionless .	the physical origin of these singularities is either a set of gauge bosons becoming massless or an entire string becoming tensionless .
more recently , convolutional neural networks have achieved unprecedented performance in a wide range of image classification problems .	recently , convolutional neural networks have been deployed successfully in a variety of applications , including imagenet classication .
therefore leniency is less vulnerable towards misleading stochastic rewards .	however , this approach can leave agents vulnerable towards misleading stochastic rewards .
an abstract system describes a mathematical model of a system behaviour 1 .	an abstract system describes a mathematical model of a system behaviour 2 .
this means that the lvb is undefined for many real-world networks that model jpds with zero probabilities , such as munin networks .	lvb is undefined for many real-world networks that model jpds with zero probabilities , such as munin networks .
therefore , many localization systems have been proposed , including the gps system , infrared-based systems .	many localization systems have been proposed over the years including the gps system .
recently several works have investigated relaying performance at the mac layer .	recently , several works have investigated relaying at the network level .
the expectation-maximization algorithm is one of the most widely used heuristics for maximizing likelihood in statistical models with latent variables .	the expectation maximization algorithm is a widely used algorithm for likelihood maximization of these kinds of models .
word2vec skip-gram is a widely used algorithm to obtain pretrained vector representations for input words .	word2vec is an unsupervised algorithm which obtains word representations by using the representations to predict context words .
generative adversarial networks , first introduced by , have become an important technique for learning generative models from complicated real-life data .	generative adversarial networks have recently become a prominent method to learn high-dimensional probability distributions .
the performance of object detectors has been dramatically improved thanks to the advance of deep convolutional neural networks .	recent years , deep convolutional neural networks lead to a series breakthroughs for image classification .
interactive zero-knowledge with restricted random oracles .	bounded-concurrent secure two-party computation without setup assumptions .
for any hilbert space h we denote the row and the column hilbert space on h by hr and hc , respectively .	for any hilbert space h we denote by bounded linear operators on h .
for recnet , we adopt the u-net architecture which has the same structure with flownet .	we use the u-net based pix2pix generative network architecture for g for d .
unitary representations of the classical groups .	natural kernels on pseudo-riemannian symmetric spaces .
some major breath vocs have already been investigated in this form , eg , during rest and exercise conditions or exposure scenarios .	some major breath constituents have already been investigated in this form , eg , during exercise conditions or exposure scenarios .
adversarial perturbations were first proposed by szegedy et al using an l-bfgs based optimization scheme , followed by fast gradient sign method .	szegedy et al first showed the existence of adversarial perturbations in cnns and proposed a l-bfgs based optimization scheme to generate the same .
the key performance indicator of 1 ms over-the-air latency has been proposed as one of the core 5g requirements by such standards bodies as the itu as well as recent studies such as those carried out under the metis 2020 project .	specifically , the key performance indicator of 1 ms over-the-air latency has been proposed by such standards bodies as the itu , as well as recent studies such as those carried out under the metis 2020 project , as one of the core 5g requirements .
deep neural networks have shown significant improvements in many application domains , ranging from computer vision .	convolutional neural networks have achieved state-of-the-art accuracy in computer vision tasks such as image recognition .
we observe pronounced spectral weight both in the anti-nodal and nodal regions .	we see well developed spectral weight in the nodal regions .
in this paper , we have assumed equal average power constraint for both the users .	throughout the paper , we assume that stbcs for both the users have the same dimensions .
the element a1 is called the multiplicity of s .	its multiplicity is the number of length n paths from the marked point to it .
deep convolutional neural networks have made significant breakthroughs in many visual understanding tasks including image classification .	in recent years , convolutional neural networks have become the de facto standard in many computer vision tasks , such as image classification and object detection .
kirkpatrick et al proposed an elastic weight consolidation mechanism that quantifies the relevance of parameters to a particular task and correspondingly adjusts the learning rate .	kirkpatrick et al have used a fisher information matrix based regularizer to slow down learning on network weights which correlate with previously acquired knowledge .
a problem that graph isomorphism reduces to is called isomorphism hard .	every isomorphism is a semi-stable cokernel .
several research groups have recently shown that convnets outperform classical approaches for object classification or detection that are based on hand-crafted features .	several research groups have shown that convnets outperform more classical approaches for object classification or detection that are based on handcrafted features .
thanks to these properties , the fw representation provides the best possibility to obtain a meaningful classical limit of relativistic qm not only for the stationary case .	thanks to these properties , the fw representation provides the best possibility of obtaining a meaningful classical limit of relativistic qm not only for the stationary case .
the lightest neutralino is the wino which is a good candidate of the cold dark matter assuming the non-thermal production from the gravitino decay .	the neutralino is a majorana particle and therefore its own antiparticle .
beside the psnr accuracy measure , we also report the structure similarity measure and running time of the sisr algorithms .	besides using the fcn score and the segmentation score , we also calculate the psnr and the ssim for a quantitative evaluation .
an isomorphism is a bijective homomorphism .	a coherent sheaf f is called reflexive if θ is an isomorphism .
we employed the perdew-burke-ernzerhof exchange correlation functional in the generalized gradient approximation .	we used the generalized gradient approximation of perdew , burke and ernzerhof .
on the other hand , post-lie algebras have been introduced by vallette in connection with the homology of partition posets and the study of koszul operads .	post-lie algebras and post-lie algebra structures recently have been introduced in connection with homology of partition posets and the study of koszul operads .
furthermore , let ψ and φ be mutually local homogeneous gn-vertex operators on w .	let ψ , φ be mutually local homogeneous gn-vertex operators .
deep learning has also shown good results in generative modeling with techniques such as variational auto-encoders .	deep learning has also resulted in fast progress in generative models which are able to generate samples from complex image distributions .
network-related techniques try to exploit idle and deep sleep opportunities , and so on .	network-related techniques try to exploit idle and deep sleep opportunities and so on .
note that computing spectral norm of a tensor is np-hard .	as shown in , it is np-hard to compute extreme eigenvalues of tensors .
we begin this section by recalling the notion of a 2-hilbert space due to baez .	we begin by summarizing some basic aspects of the theory of 2-hilbert spaces , as developed by baez .
the resulting curve is called a trajectory in phase space .	thus , in the phase space there is a reciprocal model with constant of motion h and the hamiltonian k .
from this it can be seen how consistently mcmc found the location of the posterior distribution for sampling , regardless of the initial random seed .	this demonstrates that the posterior distribution is located and well sampled , regardless of the initial random seed .
goodfellow et al proposed the fast gradient sign method , a one-step method that could generate adversarial examples .	goodfellow et al introduced the fast gradient sign method to find adversarial perturbations .
once again , we can show that dropping the restriction of akin patterns leads to hardness for both union-freedom and rewriting using views .	we show next that relaxing the extended skeleton restrictions leads to hardness for union-freedom and rewriting using views .
the estimation of these models is usually done using the em algorithm .	it is possible to fit these models to empirical data via maximum likelihood estimation .
therefore , in all the following , we focus on the linearly polarized state and study how both the mean field ax and the orthogonal vacuum field ay may be squeezed .	in the second part , we focus on the case in which the polarization remains linear and show that both the linearly polarized field mode and the orthogonal vacuum mode are squeezed .
in , caffarelli and vasseur proved the global regularity of weak solutions with l 2 data .	in , caffarelli and vasseur established the global regularity of weak solutions associated to l 2 initial data .
thus , problem 4 is a differenceof-convex programming problem and can be solved based on the convex-concave procedure .	thus , is not a convex optimization problem , but it can be efficiently solved by difference of convex programming and a convexconcave procedure similar to .
krykhtin , quartet unconstrained formulation for massless higher spin fields , nucl .	reshetnyak , brst approach to lagrangian construction for fermionic higher spin fields in ads space , nucl .
inspired by infogan , we develop a denoising framework by adding some auxiliary random noise to the input images .	inspired by infogan , we maximize the mutual information between all the latent codes and the generated images .
hence these operators are said to be primary .	it is obvious that these transformations can be coherent or not .
let us now add the assumption of semisimplicity .	let us now consider the degenerate situation .
number of data , background and signal events after all selections for different lq signals .	number of data , background and signal events after different selections .
finally , we report the transferability results by fine-tuning the networks for coco object detection .	we perform data distillation for object detection on the coco dataset .
quantum electrodynamics is a u acting as the source of aµ is a point particle .	quantum electrodynamics is the simplest quantum field theory which is physically realized .
in this case , however , even after transforming back to the fourier domain and unweighting , the residuals remain much larger than for the other weighting methods .	transforming back to the fourier domain and unweighting yields residuals that are nearly as low as the uniform weighting case .
these smoothing results have been used in for developing a kind of a δ-entropy test for discontinuous solutions by using techniques of smooth deformations .	these smoothing results have been used in for developing some δ-entropy concepts for discontinuous solutions by using techniques of smooth deformations .
in , the rate-delay trade-off of a three-node nanonetwork was analyzed for a specific messenger molecule , polyethylene , and network coding at the relay node .	in , the rate-delay trade-off of a three-node nanonetwork for a specific messenger molecule , polyethylene , was analyzed for network coding at the relay node .
enabling consumers to employ effective aggregators .	granting consumers control over their data .
let us explain the details of this mechanism .	we now want to explore these matrices in more detail .
in this paper , we introduce a detector based on the recently proposed deep residual networks .	due to its state-of-the-art performance , in this paper , we use a residual network for the detection .
the outage probability of a randomly deployed users noma is studied in , which is shown that noma enhances the outage performance of the system in comparison with orthogonal multiple access systems .	the performance of noma with randomly deployed users in a downlink scenario was investigated in , which shows that noma can outperform conventional orthogonal multiple access in terms of outage performance and ergodic sum rates .
the networks are composed of two stacked vgg16-like networks , omitting the fullyconnected layers .	both networks share the feature extraction layers which are based on vgg architecture .
later , linear network coding was proved to be able to achieve the optimal data transmission rate in an acyclic multicast network .	in subsequent works it has been shown that linear network coding is sufficient to achieve the capacity of multicast networks .
for imagenet , we use 500-dimensional word vectors trained by the skip-gram model .	specifically , we use word2vec to convert each word in a description to a 300-dimensional vector .
millimeter wave communication is a promising technology for addressing the high throughput requirement for the fifth generation mobile networks .	wireless network densification is viewed as a promising approach to enable a 1000x improvement in wireless cellular network capacity .
see and the reference therein for more applications of liouville systems .	for applications of liouville systems , see and the references therein .

it plays an important role in various fields such as the thermodynamics and so on .

it is an important aspect in many research fields such as low-temperature thermodynamics .

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

with the development of machine learning technologies , deep neural networks have shown their extraordinary performance for their high accuracy and excellent scalability .

the ordinate is the phase with 0 0 value corresponding to the deeper eclipse .

the ordinate is the flux normalized to the maximum .

huisken-ilmanen extended the imcf using geometric measure theory to prove the penrose conjecture .

huisken-ilmanen used imcf in the asymptotically flat manifolds to prove the penrose inequality .

we initialize the parameters in the convolutional and fully connected layers by following the proposed scheme in glorot and bengio .

all trainable parameters in our model are initialized by the method described by glorot and bengio .

deep convolutional neural networks achieve impressive performance on many computer vision tasks , including image classification .

deep neural networks have demonstrated significant performance improvements in a wide range of computer vision tasks .

generative adversarial nets are widely applied in generative models and have outstanding performance .

generative models , eg , variational auto-encoder , generative adversarial networks , provide a promising solution to this problem .

quantum computation is a catch-all for several models of computation based on a theoretical ability to manufacture , manipulate and measure quantum states .

quantum computation consists of single-qubit measurements on the graph states and every quantum algorithm is encoded in a measurement blueprint .

at the same time our simulation show that the structural phase transition will lead to the saturation of the number of alloying au atoms .

furthermore , our simulation shows that the structural phase transition will lead to the saturation of the number of alloying au atoms .

the approximation developed is based on the concept of decoding cells introduced in .

the approximation is based on the concept of decoding cells introduced in .

we also find that effective susy breaking scale observed on our wall becomes exponentially small as the distance between two walls grows .

we also find that effective susy breaking scale becomes exponentially small as the distance between two walls grows .

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 .

neural network learning has become a key practical machine learning approach and has achieved remarkable success in a wide range of real-world domains , such as computer vision , speech recognition , and game playing .

deep neural networks achieve near-human accuracy on many perception tasks .

deep neural networks play important roles in various computer vision tasks , eg , depth estimation .

for a k-algebra a , we denote by mod a the category of right a-modules , and denote by proj a for the induced derived functor .

let a be an affine hopf k-algebra which is a finite module over its center .

in section 2 we recall fundamental facts about g-covering functors from .

in section 3 we recall the definition and characterizations of orbit category from .

the communication capacity between job processes of a round-robin cpu scheduler was studied in .

a covert channel between two job processes sharing a round robin scheduler was studied in .

when b is a dense dcl-independent subset of a , the pair has elimination of imaginaries by .

again , note that when b is a dense dcl-independent subset of a , the pair has elimination of imaginaries by .

deep convolutional neural networks have achieved state-of-the-art performance on several image processing and computer vision tasks like image classification , object detection , and segmentation .

deep convolutional neural networks have rapidly matured as an effective tool for almost all computer vision tasks , including object recognition , classification , segmentation , superresolution , etc .

approximation algorithms for concave cost network flow problems .

solution methods for nonconvex network flow problems .

chen et al proposed gated recursive neural network to model feature combinations of context characters .

chen et al proposed gated recursive neural networks to model feature combinations .

currently , we claim this relation as a conjecture , however , we expect that a complete proof could be obtained by a rather straightforward generalization of the results of , devoted to discrete-spin models connected with the slalgebra .

we expect that a complete proof could be obtained by a rather straightforward generalization of the results of , devoted to discrete-spin models connected with the slalgebra .

the electron-ion interaction is described by the projected augmented wave potentials .

the exchange and correlation effect among electrons is described with the generalized gradient approximation .

for exchange and correlation the localdensity approximation , parametrized by perdew , burke and ernzerhof , was used .

the exchange and correlation energies were considered in the generalized gradient approximation following the perdew-burkeernzerhof parametrization scheme .

a monoid is a commutative semi-group with a unit .

an associative polyadic system with identity is called a polyadic monoid .

the entropy dissipation can be bounded from below by the relative entropy by means of the convex sobolev inequality .

a convex sobolev inequality with the auxiliary functional as its relative fisher information finally yields the exponential decay of the relative entropy .

deep neural networks have been widely applied in various fields , including computer vision he et al , among many others .

since 2012 , neural networks and deep architectures have proven very effective in application areas such as computer vision .

one of the most natural extensions of the standard model of particle physics is supersymmetry .

supersymmetry is generally regarded as one of the likely extensions to the standard model of particle physics .

tem micrograph of hgte nanoparticles , inset the diffraction pattern .

tem micrograph of hgte - ssdna complex nanostars , inset the diffraction pattern .

since the deuteron is the simplest nucleus containing a neutron , the process of pion production on the deuteron can be used for examining pion production on a neutron .

indeed , because the deuteron is a loosely bound system , one might expect to learn a host of spin-dependent properties of the neutron and proton as free particles .

this explains the close relation between the abjm theory and the theory for d-branes on the conifold .

this gives the theory of that lives 1 on n d3-branes sitting at the conifold singularity of a calabi-yau three-fold .

there was no steady input of energy and no obvious dissipation .

again there was no steady input of energy and no obvious dissipation .

this research has made use of the simbad database , operated at cds , strasbourg , france .

this work has made use of services produced by the michelson science center at the california institute of technology .

since the 1d profile is a reasonable proxy for the 3d profiles , the transmission spectra look very similar .

a profile is a finite list of linear orders on the alternatives which represent the individual choices .

however , it is shown in that this assumption is reasonable for parameter estimation over sparse binary matrices .

however , it is shown in that this assumption is reasonable for parameter estimation over ldpc codes .

reddit is a news aggregation website and online social platform launched in 2005 by steve huffman and alexis ohanian .

reddit is a news aggregation website and online social platform , which was launched in 2005 by steve huffman and alexis ohanian .

the number of collaboration in science has been steadily increasing for decades .

the characteristic collaboration size in science has been steadily increasing over the last century .

it has been convincingly argued that the physical origin of these singularities is either a set of gauge bosons becoming massless or an entire string becoming tensionless .

the physical origin of these singularities is either a set of gauge bosons becoming massless or an entire string becoming tensionless .

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

recently , convolutional neural networks have been deployed successfully in a variety of applications , including imagenet classication .

therefore leniency is less vulnerable towards misleading stochastic rewards .

however , this approach can leave agents vulnerable towards misleading stochastic rewards .

an abstract system describes a mathematical model of a system behaviour 1 .

an abstract system describes a mathematical model of a system behaviour 2 .

this means that the lvb is undefined for many real-world networks that model jpds with zero probabilities , such as munin networks .

lvb is undefined for many real-world networks that model jpds with zero probabilities , such as munin networks .

therefore , many localization systems have been proposed , including the gps system , infrared-based systems .

many localization systems have been proposed over the years including the gps system .

recently several works have investigated relaying performance at the mac layer .

recently , several works have investigated relaying at the network level .

the expectation-maximization algorithm is one of the most widely used heuristics for maximizing likelihood in statistical models with latent variables .

the expectation maximization algorithm is a widely used algorithm for likelihood maximization of these kinds of models .

word2vec skip-gram is a widely used algorithm to obtain pretrained vector representations for input words .

word2vec is an unsupervised algorithm which obtains word representations by using the representations to predict context words .

generative adversarial networks , first introduced by , have become an important technique for learning generative models from complicated real-life data .

generative adversarial networks have recently become a prominent method to learn high-dimensional probability distributions .

the performance of object detectors has been dramatically improved thanks to the advance of deep convolutional neural networks .

recent years , deep convolutional neural networks lead to a series breakthroughs for image classification .

interactive zero-knowledge with restricted random oracles .

bounded-concurrent secure two-party computation without setup assumptions .

for any hilbert space h we denote the row and the column hilbert space on h by hr and hc , respectively .

for any hilbert space h we denote by bounded linear operators on h .

for recnet , we adopt the u-net architecture which has the same structure with flownet .

we use the u-net based pix2pix generative network architecture for g for d .

unitary representations of the classical groups .

natural kernels on pseudo-riemannian symmetric spaces .

some major breath vocs have already been investigated in this form , eg , during rest and exercise conditions or exposure scenarios .

some major breath constituents have already been investigated in this form , eg , during exercise conditions or exposure scenarios .

adversarial perturbations were first proposed by szegedy et al using an l-bfgs based optimization scheme , followed by fast gradient sign method .

szegedy et al first showed the existence of adversarial perturbations in cnns and proposed a l-bfgs based optimization scheme to generate the same .

the key performance indicator of 1 ms over-the-air latency has been proposed as one of the core 5g requirements by such standards bodies as the itu as well as recent studies such as those carried out under the metis 2020 project .

specifically , the key performance indicator of 1 ms over-the-air latency has been proposed by such standards bodies as the itu , as well as recent studies such as those carried out under the metis 2020 project , as one of the core 5g requirements .

deep neural networks have shown significant improvements in many application domains , ranging from computer vision .

convolutional neural networks have achieved state-of-the-art accuracy in computer vision tasks such as image recognition .

we observe pronounced spectral weight both in the anti-nodal and nodal regions .

we see well developed spectral weight in the nodal regions .

in this paper , we have assumed equal average power constraint for both the users .

throughout the paper , we assume that stbcs for both the users have the same dimensions .

the element a1 is called the multiplicity of s .

its multiplicity is the number of length n paths from the marked point to it .

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

in recent years , convolutional neural networks have become the de facto standard in many computer vision tasks , such as image classification and object detection .

kirkpatrick et al proposed an elastic weight consolidation mechanism that quantifies the relevance of parameters to a particular task and correspondingly adjusts the learning rate .

kirkpatrick et al have used a fisher information matrix based regularizer to slow down learning on network weights which correlate with previously acquired knowledge .

a problem that graph isomorphism reduces to is called isomorphism hard .

every isomorphism is a semi-stable cokernel .

several research groups have recently shown that convnets outperform classical approaches for object classification or detection that are based on hand-crafted features .

several research groups have shown that convnets outperform more classical approaches for object classification or detection that are based on handcrafted features .

thanks to these properties , the fw representation provides the best possibility to obtain a meaningful classical limit of relativistic qm not only for the stationary case .

thanks to these properties , the fw representation provides the best possibility of obtaining a meaningful classical limit of relativistic qm not only for the stationary case .

the lightest neutralino is the wino which is a good candidate of the cold dark matter assuming the non-thermal production from the gravitino decay .

the neutralino is a majorana particle and therefore its own antiparticle .

beside the psnr accuracy measure , we also report the structure similarity measure and running time of the sisr algorithms .

besides using the fcn score and the segmentation score , we also calculate the psnr and the ssim for a quantitative evaluation .

an isomorphism is a bijective homomorphism .

a coherent sheaf f is called reflexive if θ is an isomorphism .

we employed the perdew-burke-ernzerhof exchange correlation functional in the generalized gradient approximation .

we used the generalized gradient approximation of perdew , burke and ernzerhof .

on the other hand , post-lie algebras have been introduced by vallette in connection with the homology of partition posets and the study of koszul operads .

post-lie algebras and post-lie algebra structures recently have been introduced in connection with homology of partition posets and the study of koszul operads .

furthermore , let ψ and φ be mutually local homogeneous gn-vertex operators on w .

let ψ , φ be mutually local homogeneous gn-vertex operators .

deep learning has also shown good results in generative modeling with techniques such as variational auto-encoders .

deep learning has also resulted in fast progress in generative models which are able to generate samples from complex image distributions .

network-related techniques try to exploit idle and deep sleep opportunities , and so on .

network-related techniques try to exploit idle and deep sleep opportunities and so on .

note that computing spectral norm of a tensor is np-hard .

as shown in , it is np-hard to compute extreme eigenvalues of tensors .

we begin this section by recalling the notion of a 2-hilbert space due to baez .

we begin by summarizing some basic aspects of the theory of 2-hilbert spaces , as developed by baez .

the resulting curve is called a trajectory in phase space .

thus , in the phase space there is a reciprocal model with constant of motion h and the hamiltonian k .

from this it can be seen how consistently mcmc found the location of the posterior distribution for sampling , regardless of the initial random seed .

this demonstrates that the posterior distribution is located and well sampled , regardless of the initial random seed .

goodfellow et al proposed the fast gradient sign method , a one-step method that could generate adversarial examples .

goodfellow et al introduced the fast gradient sign method to find adversarial perturbations .

once again , we can show that dropping the restriction of akin patterns leads to hardness for both union-freedom and rewriting using views .

we show next that relaxing the extended skeleton restrictions leads to hardness for union-freedom and rewriting using views .

the estimation of these models is usually done using the em algorithm .

it is possible to fit these models to empirical data via maximum likelihood estimation .

therefore , in all the following , we focus on the linearly polarized state and study how both the mean field ax and the orthogonal vacuum field ay may be squeezed .

in the second part , we focus on the case in which the polarization remains linear and show that both the linearly polarized field mode and the orthogonal vacuum mode are squeezed .

in , caffarelli and vasseur proved the global regularity of weak solutions with l 2 data .

in , caffarelli and vasseur established the global regularity of weak solutions associated to l 2 initial data .

thus , problem 4 is a differenceof-convex programming problem and can be solved based on the convex-concave procedure .

thus , is not a convex optimization problem , but it can be efficiently solved by difference of convex programming and a convexconcave procedure similar to .

krykhtin , quartet unconstrained formulation for massless higher spin fields , nucl .

reshetnyak , brst approach to lagrangian construction for fermionic higher spin fields in ads space , nucl .

inspired by infogan , we develop a denoising framework by adding some auxiliary random noise to the input images .

inspired by infogan , we maximize the mutual information between all the latent codes and the generated images .

hence these operators are said to be primary .

it is obvious that these transformations can be coherent or not .

let us now add the assumption of semisimplicity .

let us now consider the degenerate situation .

number of data , background and signal events after all selections for different lq signals .

number of data , background and signal events after different selections .

finally , we report the transferability results by fine-tuning the networks for coco object detection .

we perform data distillation for object detection on the coco dataset .

quantum electrodynamics is a u acting as the source of aµ is a point particle .

quantum electrodynamics is the simplest quantum field theory which is physically realized .

in this case , however , even after transforming back to the fourier domain and unweighting , the residuals remain much larger than for the other weighting methods .

transforming back to the fourier domain and unweighting yields residuals that are nearly as low as the uniform weighting case .

these smoothing results have been used in for developing a kind of a δ-entropy test for discontinuous solutions by using techniques of smooth deformations .

these smoothing results have been used in for developing some δ-entropy concepts for discontinuous solutions by using techniques of smooth deformations .

in , the rate-delay trade-off of a three-node nanonetwork was analyzed for a specific messenger molecule , polyethylene , and network coding at the relay node .

in , the rate-delay trade-off of a three-node nanonetwork for a specific messenger molecule , polyethylene , was analyzed for network coding at the relay node .

enabling consumers to employ effective aggregators .

granting consumers control over their data .

let us explain the details of this mechanism .

we now want to explore these matrices in more detail .

in this paper , we introduce a detector based on the recently proposed deep residual networks .

due to its state-of-the-art performance , in this paper , we use a residual network for the detection .

the outage probability of a randomly deployed users noma is studied in , which is shown that noma enhances the outage performance of the system in comparison with orthogonal multiple access systems .

the performance of noma with randomly deployed users in a downlink scenario was investigated in , which shows that noma can outperform conventional orthogonal multiple access in terms of outage performance and ergodic sum rates .

the networks are composed of two stacked vgg16-like networks , omitting the fullyconnected layers .

both networks share the feature extraction layers which are based on vgg architecture .

later , linear network coding was proved to be able to achieve the optimal data transmission rate in an acyclic multicast network .

in subsequent works it has been shown that linear network coding is sufficient to achieve the capacity of multicast networks .

for imagenet , we use 500-dimensional word vectors trained by the skip-gram model .

specifically , we use word2vec to convert each word in a description to a 300-dimensional vector .

millimeter wave communication is a promising technology for addressing the high throughput requirement for the fifth generation mobile networks .

wireless network densification is viewed as a promising approach to enable a 1000x improvement in wireless cellular network capacity .

see and the reference therein for more applications of liouville systems .

for applications of liouville systems , see and the references therein .