HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
since graphene is a low dimensional system , we expect the electron-electron interaction should play some role .	graphene is the first atomic monolayer structure fabricated experimentally .
the recent emergence of deep convolutional neural networks has provided some attractive solutions for domain transfer .	neural networks have attracted a significant amount of research interest in recent years due to the success of deep neural networks .
stargan overcomes both limitations by learning one single generator for all domain pairs of interest .	stargan alleviates the above problem by learning a unified structure .
sullivan proved that for any two analytic orientation preserving circle expanding endomorphisms f and g of the same degree , the conjugacy is analytic if , and only if , the conjugacy is absolutely continuous .	later , in , shub and sullivan proved that for any two analytic orientation preserving circle expanding endomorphisms f and g of the same degree , the conjugacy is analytic if , and only if , the conjugacy is absolutely continuous .
another interesting and important problem would be the consideration of network dynamics for epidemic models with temporary immunity .	another interesting and important problem would be the consideration of network dynamics for epidemic models with temporary im- munity .
recent advances in semantic segmentation are mainly driven by powerful deep neural network architectures .	modern segmentation techniques utilize deep convolutional neural networks and outperform the traditional approaches by a large margin .
the hamiltonian of the system consists of the following operators .	the hamiltonian of the system is a function defined on the classical phase space that takes values on operators of the hilbert space of the quantum system .
the second one is that in the next section we are going to solve the killing equation for maximally symmetric spacetimes , which result to be those that admit the maximum number of solutions .	one is that in this section we are going to construct special tensors on spacetimes admitting killing spinors and therefore we are interested in knowing to which cases the construction applies .
a wave front-based gaussian beam method for computing high fre quency waves .	a level set based eulerian method for paraxial multivalued traveltimes .
spike sorting , thus , refers to the grouping of spikes according to each neuron , from the recording of the microelectrodes .	spike sorting , thus , refers to the grouping of spikes according to each neuron , from the recording of the microelectrode .
a number of studies has demonstrated that stabilizing selection for particular phenotypes leads to emergence of this high robustness , strongly facilitated by the high amount of neutrality contained in the fitness landscapes of complex regulatory networks .	a number of studies has demonstrated that stabilizing selection for particular phenotypes leads to emergence of this high robustness , strongly fascilitated by the high amount of neutrality contained in the fitness landscapes of complex regulatory networks .
during the past two decades , a particular attention has been paid to random networks which can capture major structural properties of complex systems .	recently , much effort has been put into investigation of network systems , in order to recognize their structures and emerging complex properties .
in particular , convolutional neural networks are widely used for imaging tasks such as classification and segmentation .	deep neural networks are the state-of-the-art for supervised learning in computer vision and medical imaging tasks such as image classification .
modern neural networks have achieved superior results in classification problems recently .	recent success in computer vision and image retrieval are closely related to convolutional neural networks .
our main result is the following theorem , which is proved in the next subsection .	the proof of this theorem is contained in the next subsubsection .
thus , our noncommutative resolutions should correspond , via the isomorphism , to those considered by boyarchenko .	we expect that , in the special case of subregular nilpotent elements , our constructuion of noncommutative resolution reduces to that of boyarchenko .
the model is useful for studying time series data that exhibits long-range dependence properties .	like the discrete-time arfima model , the carfima model is useful for studying time series with short memory , long memory and antipersistence .
specifically , the theory in relies heavily on a explicit factorization of the enhanced matrix , which is only available when the number of discontinuities are finite and well separated .	the approach in relies on an explicit low-rank factorization of the lifted matrix in terms of vandermonde-like matricies , which is not available in our setting .
therefore , a dislocation is a defect breaking locally the translation invariance in the core region .	a dislocation is the topological defect of a crystal lattice .
at this concentration , the light scattering experiments show that laponite structure functions are still evolving 500 h after the preparation .	at this concentration , the light scattering experiments show that laponite structure functions are still evolving 500h after the preparation .
the spacetime is a perturbed friedmann-robertson-walker universe .	this space-time is a special case of hypersurface m 4 of the line element is the scale factor .
it has been observed that the testing accuracy even the training accuracy becomes saturated then degrades rapidly as plain networks goes deeper , which is called as the degradation problem .	the degradation problem has been observed that the testing accuracy even the training accuracy becomes saturated then degrades rapidly as plain networks go deeper .
the geometry associated with the scalars in this model is known as special geometry .	this geometry is the one for which the permeation mode is expected .
goncharov , these proceedings and references therein .	isenhower , these proceedings and references therein .
the akaike information criterion is the most well-known and commonly used model selection criterion .	one of the most commonly used information criterion is the akaike information criterion proposed by akaike .
goodin , yx luo , jk hwang , av ramayya , jh hamilton , jo rasmussen , sj zhu , a .	gelberg , jh hamilton , av ramayya , jk hwang , sj zhu , pm gore , d .
notably , krizhevsky et al achieved great progress in the image classification task with large and deep supervised cnn training .	in , krizhevsky et al trained a large deep cnn on the imagenet dataset and achieved a performance leap on the classification problem .
we use the gibbs sampling algorithm to approximate the posterior distribution q .	for algorithm 2 , we obtain the posterior distribution q mn using the laplace approximation .
figure 15 compares the rber achieved by remar to that of the state-of-the-art read reference voltage tuning technique designed for planar nand flash memory .	figure 12 compares the rber obtained by using lavar to that obtained by using an existing read reference voltage tuning technique designed for planar nand flash memory .
when the symmetry algebra is the standard , globally well-defined bms algebra , we show that the extension vanishes .	we assume that the symmetry algebra is the galois 2 field analog of the superalgebra osp .
rossmann , spectral problems with corner singularities of solutions to elliptic equations , math .	rossmann , elliptic boundary value problems in domains with point singularities , math .
superscripts denote time and subscripts location relative to the current cell .	where the superscripts denote the ith-loop order .
in , jaderberg et al develop a powerful convolutional neural network to recognize english text by regarding every english word as a class .	jaderberg et al address text recognition with a 90k-class convolutional neural network , where each class corresponds to an english word .
generative adversarial networks has shown remarkable performance improvement in various computer vision tasks , especially image-to-image translation , in recent years .	generative adversarial networks have shown impressive results for unsupervised learning tasks , such as image generation .
the long-wavelength properties of the ks equation are expected to behave like the kpz equation .	the crossover towards the kpz equation is clearly seen even in the smaller-size system .
the adversarial methodology to study store-and-froward routing in wired networks was proposed by andrews et al .	the adversarial methodology to study store-and-forward routing in wired networks was proposed by andrews et al .
the pbe form of the generalized gradient approximation was used as exchange and correlation functional .	the perdew , burke and ernzerhof parametrisation of the generalised gradient approximation was employed to describe the exchange correlation function .
the ordinate is the portion of the integrated flux of the source found by the source finder .	the ordinate is the stellar mass of galaxies .
we discuss all these aspects in some details in this section .	precisely how this happens is what we address in this section .
we further elucidate the equilibrium state space geometry of these black holes for several charge configurations .	we now investigate the phase structure of single charge black holes in the grand canonical ensemble .
the details for the other methods mentioned have been discussed in .	a more detailed discussion on mil and the assumptions involved can be found in .
the calculations were performed using first-principles density functional theory as implemented in the vienna ab initio simulation package .	all the dft calculations were performed with the ab-initio simulation package vasp using the projector augmented wave method .
significant progresses have been achieved with the development of convolutional neural network .	of particular interest are methods that use convolutional neural networks .
iii we consider models in which the fermion masses are generated by the vev of only one higgs doublet .	iv we consider models in which the fermion masses are generated by the vevs of two different higgs doublets .
in a configuration of branes and strings -the quantum hall soliton -was discussed with low energy dynamics similar to those of condensed matter systems displaying the fractional quantum hall effect .	in it was conjectured that a specific assembly of d-branes and fundamental strings would have a low-energy dynamics similar to systems displaying the fractional quantum hall effect .
variational autoencoders and generative adversarial networks are the two most popular deep generative models .	the variational autoencoder framework and generative adversarial network framework have been the two dominant options for training deep generative models .
recent advances in semantic segmentation are mainly driven by powerful deep neural network architectures .	development of recent deep convolutional neural networks makes remarkable progress on semantic segmentation .
we use the adam optimizer for all the tasks , using the default hyper-parameters .	we use the adam learning method with the default hyper parameters .
in addition , we insert batch normalization layers before each activation layer .	we apply relu activation for all the hidden layers and batch normalization to the output of conv1-conv10 .
to compensate the phase noise from the laser sources , some feed-forward and feed-back carrier phase estimation algorithms have been proposed to estimate the phase of optical carriers .	to compensate the phase noise from the laser sources , some feed-forward and feed-back carrier phase recovery algorithms have been proposed to estimate the phase of optical carriers .
in order to display genomic signature , we must eliminate effects of finite sequences on suppression of nucleotide strings .	then , eliminating effects of finite sequences on suppression of nucleotide strings , we give an optimal string length to display genomic signature .
the sneutrino is a distinguishable adm candidate , oscillating and favored to have weak scale mass .	the sneutrino is the lightest standard model superparticle in the dark blue shaded region and at slight higher values of m0 , we find the sneutrino co-annihilation region .
it will sometimes be convenient to switch between streams of tuples and tuples of streams .	sometimes it will be convenient to combine multipliers with adders .
briefly , a population of rgc spiking activities was obtained by multielectrode array recordings as in .	briefly rgc spiking activity were obtained by multielectrode array recordings as in .
an orbifold is a hausdorff topological space locally modelled on rn modulo finite group actions .	theorem 2 -orbifold m is a good orbifold .
in recent years , deep convolutional neural networks have set the state-of-the-art on a broad range of computer vision tasks .	deep neural networks have shown impressive state-of-the-art results in the last years on numerous tasks and especially on image recognition .
oxygen is a good referent to use with carbon and nitrogen to test for the presence of cno processed material .	oxygen is the only element which is depleted in the metal rich regime .
for a discussion about the relationship between these two problems see the introduction of .	for a discussion about the relationship between these two problems we refer to the introduction of .
ssd discretizes the output space of bounding boxes into a set of template boxes over varying aspect ratios and scales .	ssd discretizes the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per feature map location .
unlike these low-dose artifacts originated from reduced tube current , the streaking artifacts from sparse projection views exhibit globalized artifact patterns , which is difficult to remove using conventional denoising cnns .	unlike these low-dose artifacts from reduced tube currents , the streaking artifacts originated from sparse projection views show globalized artifacts that are difficult to remove using conventional denoising cnns .
the notion of frames introduced by duffin and schaeffer , generalizes the notion of riesz bases .	frames for hilbert spaces were first formally defined by duffin and schaeffer and popularized from then on .
web-based cbir implies the use of heterogeneous image sets and this , in turn , imposes certain constraints on how the images are organized and the type of performance metrics that are applicable .	personalization with respect to the web implies heterogeneous collections of images and this , in turn , dictates certain constraints on how these images can be organized and the type of retrieval accuracy measures that can be applied to cbir performance .
density functional theory calculations for defect formation energies were performed using the vienna ab initio simulation package .	first-principles density functional theory calculations were performed using the vienna ab initio simulation package using the generalised gradient approximation of perdew , burke , and ernzerhof .
the first term on the right-hand side of the mass formula contains all spin-independent contributions , the second and the last terms describe the spin-orbit interaction , the third term is responsible for the tensor interaction , while the forth term gives the spin-spin interaction .	the first three terms in represent spin-independent corrections , the fourth and the fifth terms are responsible for the spin-orbit interaction , the sixth one is the tensor interaction and the last one is the spin-spin interaction .
this modification consists of storing the depth of the tree at each collector node .	the only modification is the increase of the current quark mass , m0 .
observe that , contrary to the semisimple case , we need to consider representations on mixed lp-spaces till the end of the proof .	even if at the end of the proof , we consider only ordinary lp-spaces , we need representations on mixed lp-spaces .
loop checking and the well-founded semantics .	the stable model semantics for logic programming .
bayesian statistical methods for genetic association studies .	bayesian model search and multilevel inference for snp association studies .
a study of various d-brane probes , in particular d7-probe branes , in this geometry was performed in .	a study of various d-brane probes , in particular d7-probe branes , in these geometries was performed in .
vermeulen , rc , ogle , pm , tran , hd , browne , iw a .	stocke , jt , morris , sl , gioia , im , maccacaro , t .
wyner introduced the wiretap channel as a discrete memoryless and possibly noisy broadcast channel , where the sender transmits confidential messages to a legitimate receiver in the presence of an eavesdropper .	taking transmission noise into consideration , wyner developed the wiretap channel , in which the transmitter exploits the two different noise processes at the receiver and opponent to transmit information securely .
deep convolutional neural networks have been proven very useful in various tasks in computer vision including classification .	convolutional neural networks have achieved significant progress in computer vision tasks such as image classification .
trees , cycle graphs , complete graphs one of the main results in this paper is in showing that any 132-representable graph is necessarily a circle graph .	word-representable graphs all graphs odd wheels w 5 , w 7 , trees , cycle graphs , complete graphs one of the main results in this paper is in showing that any 132-representable graph is necessarily a circle graph .
salakhutdinov and hinton use a deep auto-encoder for the unsupervised learning of latent semantic document bit patterns .	salakhutdinov and hinton employ unsupervised deep auto-encoders to map documents to bit patterns using semantic addressing .
the energy cutoff is the maximum energy of a plane wave that can be represented using such a grid 38 r .	the energy cutoff is the same employed in the compete and pdg analyses .
nonparametric independence screening in sparse ultra-high-dimensional additive models .	sure independence screening in generalized linear models with np-dimensionality .
therefore , single-cell force spectroscopy was utilized for determination of the force .	therefore , single-cell force spectroscopy was utilized to determine the force .
deep neural networks have made great strides in many computer vision tasks such as image classification .	convolutional neural networks have been extremely successful across many domains in machine learning and computer vision .
during the last decade , deep learning algorithms , especially convolutional neural networks have achieved remarkable progress on numerous practical vision tasks .	in recent years , deep neural networks have achieved significant breakthroughs in many machine learning tasks .
it is manifestly supersymmetric in exactly supersymmetric theories .	interestingly , the equivalent 2d dirac theory is a supersymmetric partner of the 2d maxwell theory .
deep neural networks have been widely applied in various fields , including computer vision he et al , among many others .	large-scale deep convolutional neural networks have been successfully applied to a wide variety of applications such as image classification .
therefore , the chiral transformation of the dependent variables also becomes modified .	it turns out that the chiral transformation of the dependent variables are necessarily modified in the symmetry breaking phase .
powerful deep neural networks have been created and investigated for high-level computer vision tasks such as image classification .	convolutional neural networks have recently provided state of the art results for several recognition tasks including object recognition .
the exchange-correlation energy was evaluated with the help of the perdew-burke-erzenhof approach , within the generalised gradient approximation .	the perdew-burke-ernzerhof generalized gradient approximation was used as the exchange-correlation functional .
we use the rouge unigram statistics for performance evaluation .	we use the commonly-used rouge package to compute rouge-1 and rouge-2 scores .
deep neural networks have recently proven successful at various tasks , such as computer vision , speech recognition , and in other domains .	in recent years , deep neural networks , especially convolutional neural networks , have demonstrated highly competitive results on object recognition and image classification .
in particular , generative adversarial imitation learning is a recent al method inspired by generative adversarial networks .	generative adversarial network has become a dominant approach for learning generative models .
contact dynamics simulations of compacting cohesive granular systems .	modelling and computer simulation of granular media .
for both the predictive and retrodictive cases we are assuming that the environment is prepared in some particular state but not measured .	to obtain symmetry we would have to assume in the retrodictive case that the environment is measured to be in some state and that we have no information about its preparation .
therefore in our joint model , we apply the cost by gradient image and census transform for simplicity and sufficiency .	as a result , we apply the cost by gradient image and census transform which is used in semi-global matching for simplicity and sufficiency .
in curved spacetime , the correlation function of the cft depends on the choice of the vacuum .	in curved spacetime , the two-point function of the quantum field depends on the choice of the vacuum .
according to percolation theory , this value pc refers to the critical threshold of traffic percolation .	according to the percolation theory , this value p c refers to the critical threshold of traffic percolation .
since their introduction by engle and bollerslev , garch models have attracted much attention and have been widely investigated in the literature .	many of these patterns have been modeled using garch processes as introduced by engle and bollerslev and developed further by many other authors .
another subtle issue is the inin our support of dbc teraction between aspects and pointcuts .	a subtle issue is the question of how to count bounces at the corner between two boundaries .
a symplectic exponentially fitted modified rungekutta-nystrm method for the numerical integration of orbital problems .	a trigonometrically fitted runge-kutta method for the numerical solution of orbital problems .
the pacific northwest laboratory is a multiprogram laboratory operated by battelle memorial institute for the us department of energy under contract no .	the pacific northwest laboratory is a multi-program laboratory operated by battelle memorial institute for the us department of energy under contract de-ac0676rlo 1830 .
deep convolutional neural networks have been successfully applied to a wide range of image classification tasks .	convolutional neural networks have recently been very successful on a variety of recognition and classification tasks .
gong et al proposed a geodesic flow kernel model to overcome the limitations of unknown sampling size in sgf .	in , gong et al propose a geodesic flow kernel which models incremental changes between the source and target domains .
and a collection of 89 commercial hybrids used as genotype-dependent parameters .	and a collection of 89 commercial sunflower hybrids used as genotype-dependent parameters .
we insist , therefore , that this similarity between the distribution obtained in this model and the personal income distribution is very strict .	we confirm , therefore , that the distribution of this model has close similarity to those of personal income .

since graphene is a low dimensional system , we expect the electron-electron interaction should play some role .

graphene is the first atomic monolayer structure fabricated experimentally .

the recent emergence of deep convolutional neural networks has provided some attractive solutions for domain transfer .

neural networks have attracted a significant amount of research interest in recent years due to the success of deep neural networks .

stargan overcomes both limitations by learning one single generator for all domain pairs of interest .

stargan alleviates the above problem by learning a unified structure .

sullivan proved that for any two analytic orientation preserving circle expanding endomorphisms f and g of the same degree , the conjugacy is analytic if , and only if , the conjugacy is absolutely continuous .

later , in , shub and sullivan proved that for any two analytic orientation preserving circle expanding endomorphisms f and g of the same degree , the conjugacy is analytic if , and only if , the conjugacy is absolutely continuous .

another interesting and important problem would be the consideration of network dynamics for epidemic models with temporary immunity .

another interesting and important problem would be the consideration of network dynamics for epidemic models with temporary im- munity .

recent advances in semantic segmentation are mainly driven by powerful deep neural network architectures .

modern segmentation techniques utilize deep convolutional neural networks and outperform the traditional approaches by a large margin .

the hamiltonian of the system consists of the following operators .

the hamiltonian of the system is a function defined on the classical phase space that takes values on operators of the hilbert space of the quantum system .

the second one is that in the next section we are going to solve the killing equation for maximally symmetric spacetimes , which result to be those that admit the maximum number of solutions .

one is that in this section we are going to construct special tensors on spacetimes admitting killing spinors and therefore we are interested in knowing to which cases the construction applies .

a wave front-based gaussian beam method for computing high fre quency waves .

a level set based eulerian method for paraxial multivalued traveltimes .

spike sorting , thus , refers to the grouping of spikes according to each neuron , from the recording of the microelectrodes .

spike sorting , thus , refers to the grouping of spikes according to each neuron , from the recording of the microelectrode .

a number of studies has demonstrated that stabilizing selection for particular phenotypes leads to emergence of this high robustness , strongly facilitated by the high amount of neutrality contained in the fitness landscapes of complex regulatory networks .

a number of studies has demonstrated that stabilizing selection for particular phenotypes leads to emergence of this high robustness , strongly fascilitated by the high amount of neutrality contained in the fitness landscapes of complex regulatory networks .

during the past two decades , a particular attention has been paid to random networks which can capture major structural properties of complex systems .

recently , much effort has been put into investigation of network systems , in order to recognize their structures and emerging complex properties .

in particular , convolutional neural networks are widely used for imaging tasks such as classification and segmentation .

deep neural networks are the state-of-the-art for supervised learning in computer vision and medical imaging tasks such as image classification .

modern neural networks have achieved superior results in classification problems recently .

recent success in computer vision and image retrieval are closely related to convolutional neural networks .

our main result is the following theorem , which is proved in the next subsection .

the proof of this theorem is contained in the next subsubsection .

thus , our noncommutative resolutions should correspond , via the isomorphism , to those considered by boyarchenko .

we expect that , in the special case of subregular nilpotent elements , our constructuion of noncommutative resolution reduces to that of boyarchenko .

the model is useful for studying time series data that exhibits long-range dependence properties .

like the discrete-time arfima model , the carfima model is useful for studying time series with short memory , long memory and antipersistence .

specifically , the theory in relies heavily on a explicit factorization of the enhanced matrix , which is only available when the number of discontinuities are finite and well separated .

the approach in relies on an explicit low-rank factorization of the lifted matrix in terms of vandermonde-like matricies , which is not available in our setting .

therefore , a dislocation is a defect breaking locally the translation invariance in the core region .

a dislocation is the topological defect of a crystal lattice .

at this concentration , the light scattering experiments show that laponite structure functions are still evolving 500 h after the preparation .

at this concentration , the light scattering experiments show that laponite structure functions are still evolving 500h after the preparation .

the spacetime is a perturbed friedmann-robertson-walker universe .

this space-time is a special case of hypersurface m 4 of the line element is the scale factor .

it has been observed that the testing accuracy even the training accuracy becomes saturated then degrades rapidly as plain networks goes deeper , which is called as the degradation problem .

the degradation problem has been observed that the testing accuracy even the training accuracy becomes saturated then degrades rapidly as plain networks go deeper .

the geometry associated with the scalars in this model is known as special geometry .

this geometry is the one for which the permeation mode is expected .

goncharov , these proceedings and references therein .

isenhower , these proceedings and references therein .

the akaike information criterion is the most well-known and commonly used model selection criterion .

one of the most commonly used information criterion is the akaike information criterion proposed by akaike .

goodin , yx luo , jk hwang , av ramayya , jh hamilton , jo rasmussen , sj zhu , a .

gelberg , jh hamilton , av ramayya , jk hwang , sj zhu , pm gore , d .

notably , krizhevsky et al achieved great progress in the image classification task with large and deep supervised cnn training .

in , krizhevsky et al trained a large deep cnn on the imagenet dataset and achieved a performance leap on the classification problem .

we use the gibbs sampling algorithm to approximate the posterior distribution q .

for algorithm 2 , we obtain the posterior distribution q mn using the laplace approximation .

figure 15 compares the rber achieved by remar to that of the state-of-the-art read reference voltage tuning technique designed for planar nand flash memory .

figure 12 compares the rber obtained by using lavar to that obtained by using an existing read reference voltage tuning technique designed for planar nand flash memory .

when the symmetry algebra is the standard , globally well-defined bms algebra , we show that the extension vanishes .

we assume that the symmetry algebra is the galois 2 field analog of the superalgebra osp .

rossmann , spectral problems with corner singularities of solutions to elliptic equations , math .

rossmann , elliptic boundary value problems in domains with point singularities , math .

superscripts denote time and subscripts location relative to the current cell .

where the superscripts denote the ith-loop order .

in , jaderberg et al develop a powerful convolutional neural network to recognize english text by regarding every english word as a class .

jaderberg et al address text recognition with a 90k-class convolutional neural network , where each class corresponds to an english word .

generative adversarial networks has shown remarkable performance improvement in various computer vision tasks , especially image-to-image translation , in recent years .

generative adversarial networks have shown impressive results for unsupervised learning tasks , such as image generation .

the long-wavelength properties of the ks equation are expected to behave like the kpz equation .

the crossover towards the kpz equation is clearly seen even in the smaller-size system .

the adversarial methodology to study store-and-froward routing in wired networks was proposed by andrews et al .

the adversarial methodology to study store-and-forward routing in wired networks was proposed by andrews et al .

the pbe form of the generalized gradient approximation was used as exchange and correlation functional .

the perdew , burke and ernzerhof parametrisation of the generalised gradient approximation was employed to describe the exchange correlation function .

the ordinate is the portion of the integrated flux of the source found by the source finder .

the ordinate is the stellar mass of galaxies .

we discuss all these aspects in some details in this section .

precisely how this happens is what we address in this section .

we further elucidate the equilibrium state space geometry of these black holes for several charge configurations .

we now investigate the phase structure of single charge black holes in the grand canonical ensemble .

the details for the other methods mentioned have been discussed in .

a more detailed discussion on mil and the assumptions involved can be found in .

the calculations were performed using first-principles density functional theory as implemented in the vienna ab initio simulation package .

all the dft calculations were performed with the ab-initio simulation package vasp using the projector augmented wave method .

significant progresses have been achieved with the development of convolutional neural network .

of particular interest are methods that use convolutional neural networks .

iii we consider models in which the fermion masses are generated by the vev of only one higgs doublet .

iv we consider models in which the fermion masses are generated by the vevs of two different higgs doublets .

in a configuration of branes and strings -the quantum hall soliton -was discussed with low energy dynamics similar to those of condensed matter systems displaying the fractional quantum hall effect .

in it was conjectured that a specific assembly of d-branes and fundamental strings would have a low-energy dynamics similar to systems displaying the fractional quantum hall effect .

variational autoencoders and generative adversarial networks are the two most popular deep generative models .

the variational autoencoder framework and generative adversarial network framework have been the two dominant options for training deep generative models .

recent advances in semantic segmentation are mainly driven by powerful deep neural network architectures .

development of recent deep convolutional neural networks makes remarkable progress on semantic segmentation .

we use the adam optimizer for all the tasks , using the default hyper-parameters .

we use the adam learning method with the default hyper parameters .

in addition , we insert batch normalization layers before each activation layer .

we apply relu activation for all the hidden layers and batch normalization to the output of conv1-conv10 .

to compensate the phase noise from the laser sources , some feed-forward and feed-back carrier phase estimation algorithms have been proposed to estimate the phase of optical carriers .

to compensate the phase noise from the laser sources , some feed-forward and feed-back carrier phase recovery algorithms have been proposed to estimate the phase of optical carriers .

in order to display genomic signature , we must eliminate effects of finite sequences on suppression of nucleotide strings .

then , eliminating effects of finite sequences on suppression of nucleotide strings , we give an optimal string length to display genomic signature .

the sneutrino is a distinguishable adm candidate , oscillating and favored to have weak scale mass .

the sneutrino is the lightest standard model superparticle in the dark blue shaded region and at slight higher values of m0 , we find the sneutrino co-annihilation region .

it will sometimes be convenient to switch between streams of tuples and tuples of streams .

sometimes it will be convenient to combine multipliers with adders .

briefly , a population of rgc spiking activities was obtained by multielectrode array recordings as in .

briefly rgc spiking activity were obtained by multielectrode array recordings as in .

an orbifold is a hausdorff topological space locally modelled on rn modulo finite group actions .

theorem 2 -orbifold m is a good orbifold .

in recent years , deep convolutional neural networks have set the state-of-the-art on a broad range of computer vision tasks .

deep neural networks have shown impressive state-of-the-art results in the last years on numerous tasks and especially on image recognition .

oxygen is a good referent to use with carbon and nitrogen to test for the presence of cno processed material .

oxygen is the only element which is depleted in the metal rich regime .

for a discussion about the relationship between these two problems see the introduction of .

for a discussion about the relationship between these two problems we refer to the introduction of .

ssd discretizes the output space of bounding boxes into a set of template boxes over varying aspect ratios and scales .

ssd discretizes the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per feature map location .

unlike these low-dose artifacts originated from reduced tube current , the streaking artifacts from sparse projection views exhibit globalized artifact patterns , which is difficult to remove using conventional denoising cnns .

unlike these low-dose artifacts from reduced tube currents , the streaking artifacts originated from sparse projection views show globalized artifacts that are difficult to remove using conventional denoising cnns .

the notion of frames introduced by duffin and schaeffer , generalizes the notion of riesz bases .

frames for hilbert spaces were first formally defined by duffin and schaeffer and popularized from then on .

web-based cbir implies the use of heterogeneous image sets and this , in turn , imposes certain constraints on how the images are organized and the type of performance metrics that are applicable .

personalization with respect to the web implies heterogeneous collections of images and this , in turn , dictates certain constraints on how these images can be organized and the type of retrieval accuracy measures that can be applied to cbir performance .

density functional theory calculations for defect formation energies were performed using the vienna ab initio simulation package .

first-principles density functional theory calculations were performed using the vienna ab initio simulation package using the generalised gradient approximation of perdew , burke , and ernzerhof .

the first term on the right-hand side of the mass formula contains all spin-independent contributions , the second and the last terms describe the spin-orbit interaction , the third term is responsible for the tensor interaction , while the forth term gives the spin-spin interaction .

the first three terms in represent spin-independent corrections , the fourth and the fifth terms are responsible for the spin-orbit interaction , the sixth one is the tensor interaction and the last one is the spin-spin interaction .

this modification consists of storing the depth of the tree at each collector node .

the only modification is the increase of the current quark mass , m0 .

observe that , contrary to the semisimple case , we need to consider representations on mixed lp-spaces till the end of the proof .

even if at the end of the proof , we consider only ordinary lp-spaces , we need representations on mixed lp-spaces .

loop checking and the well-founded semantics .

the stable model semantics for logic programming .

bayesian statistical methods for genetic association studies .

bayesian model search and multilevel inference for snp association studies .

a study of various d-brane probes , in particular d7-probe branes , in this geometry was performed in .

a study of various d-brane probes , in particular d7-probe branes , in these geometries was performed in .

vermeulen , rc , ogle , pm , tran , hd , browne , iw a .

stocke , jt , morris , sl , gioia , im , maccacaro , t .

wyner introduced the wiretap channel as a discrete memoryless and possibly noisy broadcast channel , where the sender transmits confidential messages to a legitimate receiver in the presence of an eavesdropper .

taking transmission noise into consideration , wyner developed the wiretap channel , in which the transmitter exploits the two different noise processes at the receiver and opponent to transmit information securely .

deep convolutional neural networks have been proven very useful in various tasks in computer vision including classification .

convolutional neural networks have achieved significant progress in computer vision tasks such as image classification .

trees , cycle graphs , complete graphs one of the main results in this paper is in showing that any 132-representable graph is necessarily a circle graph .

word-representable graphs all graphs odd wheels w 5 , w 7 , trees , cycle graphs , complete graphs one of the main results in this paper is in showing that any 132-representable graph is necessarily a circle graph .

salakhutdinov and hinton use a deep auto-encoder for the unsupervised learning of latent semantic document bit patterns .

salakhutdinov and hinton employ unsupervised deep auto-encoders to map documents to bit patterns using semantic addressing .

the energy cutoff is the maximum energy of a plane wave that can be represented using such a grid 38 r .

the energy cutoff is the same employed in the compete and pdg analyses .

nonparametric independence screening in sparse ultra-high-dimensional additive models .

sure independence screening in generalized linear models with np-dimensionality .

therefore , single-cell force spectroscopy was utilized for determination of the force .

therefore , single-cell force spectroscopy was utilized to determine the force .

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

convolutional neural networks have been extremely successful across many domains in machine learning and computer vision .

during the last decade , deep learning algorithms , especially convolutional neural networks have achieved remarkable progress on numerous practical vision tasks .

in recent years , deep neural networks have achieved significant breakthroughs in many machine learning tasks .

it is manifestly supersymmetric in exactly supersymmetric theories .

interestingly , the equivalent 2d dirac theory is a supersymmetric partner of the 2d maxwell theory .

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

large-scale deep convolutional neural networks have been successfully applied to a wide variety of applications such as image classification .

therefore , the chiral transformation of the dependent variables also becomes modified .

it turns out that the chiral transformation of the dependent variables are necessarily modified in the symmetry breaking phase .

powerful deep neural networks have been created and investigated for high-level computer vision tasks such as image classification .

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

the exchange-correlation energy was evaluated with the help of the perdew-burke-erzenhof approach , within the generalised gradient approximation .

the perdew-burke-ernzerhof generalized gradient approximation was used as the exchange-correlation functional .

we use the rouge unigram statistics for performance evaluation .

we use the commonly-used rouge package to compute rouge-1 and rouge-2 scores .

deep neural networks have recently proven successful at various tasks , such as computer vision , speech recognition , and in other domains .

in recent years , deep neural networks , especially convolutional neural networks , have demonstrated highly competitive results on object recognition and image classification .

in particular , generative adversarial imitation learning is a recent al method inspired by generative adversarial networks .

generative adversarial network has become a dominant approach for learning generative models .

contact dynamics simulations of compacting cohesive granular systems .

modelling and computer simulation of granular media .

for both the predictive and retrodictive cases we are assuming that the environment is prepared in some particular state but not measured .

to obtain symmetry we would have to assume in the retrodictive case that the environment is measured to be in some state and that we have no information about its preparation .

therefore in our joint model , we apply the cost by gradient image and census transform for simplicity and sufficiency .

as a result , we apply the cost by gradient image and census transform which is used in semi-global matching for simplicity and sufficiency .

in curved spacetime , the correlation function of the cft depends on the choice of the vacuum .

in curved spacetime , the two-point function of the quantum field depends on the choice of the vacuum .

according to percolation theory , this value pc refers to the critical threshold of traffic percolation .

according to the percolation theory , this value p c refers to the critical threshold of traffic percolation .

since their introduction by engle and bollerslev , garch models have attracted much attention and have been widely investigated in the literature .

many of these patterns have been modeled using garch processes as introduced by engle and bollerslev and developed further by many other authors .

another subtle issue is the inin our support of dbc teraction between aspects and pointcuts .

a subtle issue is the question of how to count bounces at the corner between two boundaries .

a symplectic exponentially fitted modified rungekutta-nystrm method for the numerical integration of orbital problems .

a trigonometrically fitted runge-kutta method for the numerical solution of orbital problems .

the pacific northwest laboratory is a multiprogram laboratory operated by battelle memorial institute for the us department of energy under contract no .

the pacific northwest laboratory is a multi-program laboratory operated by battelle memorial institute for the us department of energy under contract de-ac0676rlo 1830 .

deep convolutional neural networks have been successfully applied to a wide range of image classification tasks .

convolutional neural networks have recently been very successful on a variety of recognition and classification tasks .

gong et al proposed a geodesic flow kernel model to overcome the limitations of unknown sampling size in sgf .

in , gong et al propose a geodesic flow kernel which models incremental changes between the source and target domains .

and a collection of 89 commercial hybrids used as genotype-dependent parameters .

and a collection of 89 commercial sunflower hybrids used as genotype-dependent parameters .

we insist , therefore , that this similarity between the distribution obtained in this model and the personal income distribution is very strict .

we confirm , therefore , that the distribution of this model has close similarity to those of personal income .