HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
we adopt the region proposal network from faster rcnn for the object localization .	in terms of implementation details , we use the visual features extracted from faster r-cnn .
this attractor is the same stable stationary state that one obtains starting with biological conditions described above .	this cyclic trajectory is called an attractor .
an offset correction is applied to jet energies to take the contribution from pileup interactions into account .	an offset correction is applied to jet energies to take into account the contributions from neutral particles produced in pileup interactions .
deep learning has become a highly successful machine learning method employed in a wide range of applications such as optical character recognition .	deep learning has been widely used in the fields of machine learning and pattern recognition due to its advanced classification performance .
a spanning tree is a set of arrows drawn on the lattice , such that each site has exactly one arrow pointing from the site to a neighbor , and such that there are no closed loops of arrows .	a spanning tree t is a subgraph of g with the same vertex set as g such that t contains no cycles .
this formulation is known as the eigenstate thermalization hypothesis .	the standard formulation of this belief is the eigenvector thermalization hypothesis .
in recent years , deep learning technology has attracted considerable interest in the computer vision and machine learning community .	recently , deep learning methods have made remarkable progress in computer vision and machine learning .
generalized gradient approximation by perdew , burke , and ernzerhof parametrization is employed for the exchange-correlation potential .	the generalized gradient approximation of perdew , burke and ernzerhof was employed for the exchange-correlation potential .
the wikipedia hourly visitor activity on the pages of the celebrities was used to investigate fame levels of the tennis players .	the wikipedia hourly visits on the pages of celebrities was used to investigate fame levels of tennis players .
in doing so we obtain relationships between canonical transformations in classical mechanics and quantum mechanics .	in doing so we obtain relations between classical and quantum canonical transformations .
an ontology is an explicit specification of a conceptualization of an area of interest .	an ontology can be defined as a formal , explicit specification of a shared conceptualization .
we evaluate our model on a standard benchmark for video classification , ucf-101 .	we evaluate the performance of our scheme on two standard action recognition benchmarks , namely hmdb-51 .
in previous work we have introduced a new algorithm to detect the presence of electromagnetic signals using optimum theoretic discriminators applied to wavelet transform output .	in previous work we presented a new algorithm for pulse detection using a window where either a complete pulse or noise alone is found .
we implement the resnet-101 deep architecture as the base network for the deeplab model .	the resnet50 pretrained on imagenet is employed as our initialized model .
max-pooling and dropout are used following each convolutional layer .	for regularization , dropout is applied to each layer .
the enkf follows a monte carlo approach to approximate the moments of the underlying probability distributions in the kalman filter equations .	the enkf uses a monte carlo step within the kalman filter formalism , and recursively approximates the filtering density by an ensemble .
deep learning and deep convolutional neural networks in particular , have recently shown impressive performance on a number of multimedia information retrieval tasks .	deep convolutional neural networks have achieved great success in computer vision related tasks such as image classification , and so on .
it turns out that kerr-nut-ds spacetime , in arbitrary dimension , admits a closed conformal killing-yano tensor of rank two in such background .	indeed , the class of kerr-nut-ds spacetimes in arbitrary dimension admits a tower of ky tensors that enables the analytical integration of the geodesic equation in this background .
agrawal et al used a deep neural network to predict the dynamics model of robotic arm operation .	agrawal et al constructed a joint inverse-forward model to learn feature representation for the task of pushing objects .
one residual module consists of two fully connected layers of 1024 nodes followed by batch normalization .	the convnet contained a cascade of three 2d convolutional , max-pooling connected to a fully connected layer .
we pre-train the transform network using the whole set of the celeba dataset d with about 200,000 face images .	we evaluate our method using the celeba dataset , which consists of 40 facial attribute labels and 202,599 images .
generalizing this argument gives the following easy theorem .	we summarize this result in the following theorem .
assume that the configuration space is a lie group g and denote the local coordinates in g by g .	more generally however , the configuration space is the smooth riemann surface σ .
centralized channel assignment and routing algorithms for multi-channel wireless mesh networks .	joint routing and channel assignment in multi-radio wireless mesh networks .
this approach is also considered in for multipleinput single output and mimo scenarios , respectively , with the assumption that one user is entrusted and the other is the potential eavesdropper .	this approach is also considered in for multiple-input single output and mimo scenarios , respectively , in a two-user setting , with the assumption that one user is entrusted and the other is the potential eavesdropper .
at least one of these jets must be consistent with the decay of a heavy-flavour hadron , identified by the combined secondary vertex b-tagging algorithm .	at least one of these jets must be consistent with containing the decay of a heavy-flavor hadron , as identified using the medium operating point of the combined secondary vertex b tagging algorithm .
deep neural networks have demonstrated stateof-the-art and sometimes human-competitive performance in numerous vision-related tasks .	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 .
convolutional neural networks have surpassed many traditional machine learning approaches in solving several computer vision tasks such as classification and others .	recently , deep neural networks have gained the attention of numerous researchers outperforming state-of-the-art approaches on various computer vision tasks .
a plaquette is a closed loop consists of 4 different points .	the plaquette is a piece of a curved manifold .
this is particularly relevant at high transverse momenta , where ew corrections are strongly enhanced by logarithmic contributions of sudakov type , which can reach several tens of percent at the tev scale .	moreover , ew corrections are especially relevant at the tev scale , where large logarithms of sudakov type can lead to nlo ew effects of tens of percent .
its phase space is a cylinder to a mixed regime with a large chaotic domain .	the phase space a consist of the solutions of eq .
overlaid is a band representing the maximal variation of the result under various spinalignment scenarios .	overlaid is a grid of the loci of a simple absorbed power law model as γ and nh vary .
deep learning techniques have recently enabled researchers to successfully tackle low-level perception problems in a supervised learning fashion .	most recently , the field of deep learning or deep neural networks has advanced rapidly leading to breakthroughs in both high-level and low-level vision problems .
glagolev vv , gulamov kg , kratenko myu et .	glagolev vv , gulamov kg , lipin vd et .
convolutional neural networks have achieved remarkable impact in many machine learning applications , including computer vision , natural language processing and reinforcement learning .	deep convolutional neural networks have been proven very useful in various tasks in computer vision including classification .
arenas et al detected aibo robot and humanoid robots using the cascade of boosted classifiers , which is suitable for real-time applications .	arenas et al proposed a real-time capable aibo and humanoid robot detector using a cascade of boosted classifiers .
the mapping of the ab initio data onto the effective spin hamiltonian is carried out following the procedure described in refs .	mapping of the ab initio data onto an effective spin hamiltonian is carried out following the procedure earlier used in refs .
deep neural networks have exhibited great performance in computer vision tasks in recent years .	recently , convolutional neural networks -based methods achieve great success in image classification tasks .
chrobak and sgall showed that any memoryless randomized algorithm has unbounded competitive ratio .	koutsoupias and taylor shows that any memoryless randomized algorithm has unbounded competitive ratio in this case .
indeed , as we will show in section v , string-net condensation naturally gives rise to both gauge interactions and fermi statistics .	however , we know that string-net condensation quite generally describes all lattice gauge theories with or without emergent fermi statistics .
as srcnn is less effective in the detail estimation , kim et al propose the residual learning algorithm based on a deeper network .	kim et al addressed certain limitations of srcnn with a very deep super-resolution network which can be efficiently trained relying on fast residual learning .
these slopes and is a monotonically decreasing function of γ .	their slopes are called the d regular slopes .
here we employ the power method in combination with the constrained sss samplings .	note that only one sampling is enough in the constrained sss method .
let us also insist that spacetime is a manifold .	the spacetime consists of 4 dimensional black hole with an additional -dimensional sphere .
deep neural networks have achieved state-of-the-art performance in many application areas , such as computer vision and natural language processing .	deep neural networks are powerful machine learning systems , which have been demonstrated in a variety of tasks including image classification among others .
there has been extensive discussion of the structure of fermion masses in f-theory .	recently there has been much interest in the possibility that the fermion mass structure might emerge from f-theory .
we extract visual features from the person-centric images using the alexnet convolutional network .	to evaluate the proposed toolflow , we target image classification using pretrained models on the imagenet dataset .
qubit a is the control bit for qutrit c and qubit b is the control bit for qutrit d .	qubit a is the control bit for the controlledu 2 gate , qubit b is the control bit for the controlled-u gate , and qubit c is the be the eigenstates of u with corresponding target bit for both .
electronic exchange correlation is treated under the generalised gradient approximation using perdew-burke-ernzerhof functional .	exchange and correlations are considered in the generalized gradient approximation , following the perdew-burke-ernzerhof parametrization scheme .
besides , song et al introduce the binary segmentation masks to construct synthetic rgb-mask pairs as inputs , then they design a mask-guided contrastive attention model to learn features separately from the body and background regions .	song et al introduced the binary segmentation masks to construct synthetic rgb-mask pairs as inputs , as well as a mask-guided contrastive attention model to learn features separately from body and background regions .
in this case φ is called an isomorphism of g onto h .	then this isomorphism is the identity map .
this can be achieved by the use of cmos compatible resistive crossbar memory based on ag-si memristors .	such devices can be integrated into metallic crossbars to obtain high density resistive crossbar memory .
since gravity is the universal force which couples to all energy sources , the decay of the inflaton is necessarily 3 accompanied by non-thermal emission of kk gravitons with masses comparable to mφ .	since gravity is a gauge theory , one has to take into account the complications due to the gauge fixing and ghost 19 terms .
two classes of wave packets with an arbitrarily given degree of rigidity are presented .	two classes of wave packets with an arbitrarily given degree of rigidity are given explicitly .
collell et al introduce a multi-modal recurrent neural network to generate image descriptions .	karpathy et al use deep learning to produce descriptions of images , which compete with human generated labels .
so corresponding to every two tilings of rwhere the leftmost five columns match the pattern in figure 11 , we get one tiling where the leftmost four columns match the pattern in figure 11 .	so , corresponding to each tiling of r , where the leftmost five columns match the pattern in figure 11 , we get a tiling where the leftmost four columns match the pattern in figure 11 .
statistical learning of a language model aims to approximate the probability distribution on the set of expressions in the language .	a goal of language modeling is to learn the joint probability function of sequences of words in a language .
deep neural networks have achieved tremendous success in recent years , due to the ability of these models to achieve state-of-the-art performances .	the accuracy of deep convolutional neural networks for visual categorization has advanced substantially from 2012 levels to current state-of-the-art cnns like resnet .
the surf features are shallow features extracted and quantized into an 800-bin histogram using a codebook computed with k-means on a subset of images from amazon .	these sub-datasets are based on surf features have been made by , which are extracted and quantized into an 800-bin histogram with codebooks computed with k-means on a subset of images from amazon .
the star detector consists of many detector subsystems in a large solenoidal magnet with the time projection chamber located at 18 m from the center of the tpc .	the star detector consists of a 4 2 m long cylindrical time projection chamber at 18m from the interaction point are sensitive to the neutral remnants of nuclear breakup .
originally introduced to explain the absence of charge-parity violation in strong interactions , the axion is one of the best motivated cold dark matter candidates .	the axion , a nambu-goldstone boson , is a solution to the strong cp problem of qcd and a plausible cold dark matter candidate .
in this paper , afm uses long short-term memory -recurrent neural networks .	this model is first built as a 4 layer long short-term memory -recurrent neural networks .
the data were reduced using the miriad software package .	the data underwent a standard data reduction with the miriad software package .
a g-action on x is called smart if 0 is an isomorphism .	the isomorphism is the natural , forgetful mapping sending a kasparov cycle to a kk ban-cycle .
we could say that the tf-g regime should exhibit the superfluid properties more prominently than the g-regime .	we find that the tf-g regime can exhibit the superfluid properties more prominently than the g-regime .
consider the entropy of two system copies .	consider the entropy production density of radiative transfer .
thus , in the phase space there is a reciprocal model with constant of motion h and the hamiltonian k .	in phase space there is a curve that attracts most of the trajectories .
evolutionary game theory has been introduced as a framework to study the processes of selection of genes or behaviors in biological and social systems .	evolutionary game theory is widely applied to study the maintenance of cooperation among the selfish individuals .
now we proceed on to define the cauchy elements in biquasi loops .	now we proceed on to define non-associative binear-rings .
let us check criteria is the only relevant length scale .	the criteria is the dominant part of the scalar potential during inflation is independent of the field value .
deep learning has shown its effectiveness in many computer vision tasks , such as object detection .	object recognition in large-scale image datasets has achieved impressive performance with deep convolutional neural networks .
now , we introduce the following outer bound for the capacity region of the degraded discrete memoryless multi-receiver wiretap channel with public and confidential messages .	finally , we provide an inner bound for the capacity region of the general , not necessarily degraded , gaussian mimo multi-receiver wiretap channel .
latent dirichlet allocation is a topic modeling technique for textual data .	latent dirichlet allocation is a generative probabilistic model for collections of a corpus .
now we consider the factorization of the general transfer matrix .	now we are going to consider explicit formulae for the action of these operators on polynomials .
the number of the condensed counterion nc on each plate is determined by minimizing the total free energy including fluctuation contributions .	the number of condensed counterions is determined self-consistently , by minimizing the total free energy which includes fluctuation contributions .
in this section , we introduce how scalable estimation of mutual information is performed in terms of practical scenarios via mutual information neural estimation and the deep infomax described below .	in this section , we describe the neural network proposed in for estimating mutual information based on an alternative representations of kl-divergence .
aeppli , jw lynn , pg pagliuso , jl sarrao , mf hundley , jd thompson , and z .	nicklas , no moreno , jd thompson , mf hundley , jl sarrao , and z .
for this it suffices to prove that it is a closed embedding .	so it suffices to prove that s is a state space , and convex .
however , nonlinearities from the ac power flow equations result in the ac-opf problem being nonconvex and generally np-hard .	coupling this with nonconvex ac powerflow constraints leads to a mixedinteger nonlinear programming problem that is np-hard .
if neglected , these two reactions would have the highest contribution to the error .	this means that if any of these four reactions are neglected , they would have the highest contribution to the error .
illustrate the above definition by an example .	we now illustrate this by the following example .
for the numerical integration , we provide a simple interface to integrators from the cuba library .	for multidimensional numerical integration we use the cuba library .
an alternative approach may consist in using cubic splines to approximate each set of time series but this requires the setting of knots which may a combinatory complex task .	an alternative approach in this curve clustering context may consist in using cubic splines to model each class of curves james and sugar but this requires the setting of knots a priori .
the observed smc depletions can be modeled with the scaling law if the smc abundance ratios are slightly non solar .	in conclusion , it is not possible to model the smc depletions if the smc abundances are strictly solar .
quantum statistical mechanics and galois theory .	chaotic behaviour and the einstein equations .
the total number of species in the food web denoted by s .	the fraction of omnivorous species in the food web denoted by o .
infogan learned disentangled latent space unsupervisedly by adding regularizers to the generator to maximize the mutual information .	under the unsupervised setting , infogan learned disentangled representation by maximizing the mutual information between latent code and data observation .
deep neural networks have been widely used in many artificial intelligence applications including computer vision .	deep neural networks have been successfully applied to many machine learning and statistical inference problems including speech recognition , natural language processing .
parameterized complexity of constraint satisfaction problems .	the approximability of constraint satisfaction problems .
the quantum key distribution is one of the most mature quantum cryptography technologies , which can provide information-theoretical provable security together with the one-time pad method .	among the applications of the quantum network , quantum key distribution is one of the first technology in quantum information science to produce practical applications .
for this task , we employ inceptionv3 network architecture , with pretrained weights from imagenet for initialization .	we use the output of the final global average pooling layer of inception-v3 deep learning network for the purpose .
similarly , grosse et al tested a suite of feature reduction methods specifically in the malware domain .	grosse et al proposed to use the gradient based approach to generate adversarial android malware examples .
it implies that here not only spontaneous but also stimulated emission of radiation comparable with spontaneous emission occurs .	it implies that now not only spontaneous but also stimulated emission of radiation comparable with spontaneous emission occurs .
in the sequel , f denotes a convex monotone homogeneous map that has an eigenvector .	in the sequel we shall further assume that f is a c 2 convex function , and under this assumption we shall show that such functions are precisely those decomposing as per eq .
here we note that spin reversal symmetry has not been considered explicitly in previous studies of level statistics for various quantum spin chains .	we may therefore expect that the rmt analysis of the xxz spin chains is important in discussing level statistics for other quantum systems that have some connection to an integrable system .
we first compare with a traditional regionlet method when training using small size dataset .	we first compare with traditional regionlet method when training using small size dataset .
now we give the definition of non-associative biseminear-rings .	now we proceed on to define the concept of bisemigroup birings .
other string coordinates remain unchanged .	the string coordinates and momenta remain unchanged .
now we proceed on to define smarandache non-associative near-rings .	now we proceed on to define smarandache pseudo left ideals .
for the symbol tr denotes integral constant electromagnetic fields , the integrand in explicitly .	here and below , the symbol tr denotes the contraction with respect to all repeated indices , which will not be shown explicitly .

we adopt the region proposal network from faster rcnn for the object localization .

in terms of implementation details , we use the visual features extracted from faster r-cnn .

this attractor is the same stable stationary state that one obtains starting with biological conditions described above .

this cyclic trajectory is called an attractor .

an offset correction is applied to jet energies to take the contribution from pileup interactions into account .

an offset correction is applied to jet energies to take into account the contributions from neutral particles produced in pileup interactions .

deep learning has become a highly successful machine learning method employed in a wide range of applications such as optical character recognition .

deep learning has been widely used in the fields of machine learning and pattern recognition due to its advanced classification performance .

a spanning tree is a set of arrows drawn on the lattice , such that each site has exactly one arrow pointing from the site to a neighbor , and such that there are no closed loops of arrows .

a spanning tree t is a subgraph of g with the same vertex set as g such that t contains no cycles .

this formulation is known as the eigenstate thermalization hypothesis .

the standard formulation of this belief is the eigenvector thermalization hypothesis .

in recent years , deep learning technology has attracted considerable interest in the computer vision and machine learning community .

recently , deep learning methods have made remarkable progress in computer vision and machine learning .

generalized gradient approximation by perdew , burke , and ernzerhof parametrization is employed for the exchange-correlation potential .

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

the wikipedia hourly visitor activity on the pages of the celebrities was used to investigate fame levels of the tennis players .

the wikipedia hourly visits on the pages of celebrities was used to investigate fame levels of tennis players .

in doing so we obtain relationships between canonical transformations in classical mechanics and quantum mechanics .

in doing so we obtain relations between classical and quantum canonical transformations .

an ontology is an explicit specification of a conceptualization of an area of interest .

an ontology can be defined as a formal , explicit specification of a shared conceptualization .

we evaluate our model on a standard benchmark for video classification , ucf-101 .

we evaluate the performance of our scheme on two standard action recognition benchmarks , namely hmdb-51 .

in previous work we have introduced a new algorithm to detect the presence of electromagnetic signals using optimum theoretic discriminators applied to wavelet transform output .

in previous work we presented a new algorithm for pulse detection using a window where either a complete pulse or noise alone is found .

we implement the resnet-101 deep architecture as the base network for the deeplab model .

the resnet50 pretrained on imagenet is employed as our initialized model .

max-pooling and dropout are used following each convolutional layer .

for regularization , dropout is applied to each layer .

the enkf follows a monte carlo approach to approximate the moments of the underlying probability distributions in the kalman filter equations .

the enkf uses a monte carlo step within the kalman filter formalism , and recursively approximates the filtering density by an ensemble .

deep learning and deep convolutional neural networks in particular , have recently shown impressive performance on a number of multimedia information retrieval tasks .

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

it turns out that kerr-nut-ds spacetime , in arbitrary dimension , admits a closed conformal killing-yano tensor of rank two in such background .

indeed , the class of kerr-nut-ds spacetimes in arbitrary dimension admits a tower of ky tensors that enables the analytical integration of the geodesic equation in this background .

agrawal et al used a deep neural network to predict the dynamics model of robotic arm operation .

agrawal et al constructed a joint inverse-forward model to learn feature representation for the task of pushing objects .

one residual module consists of two fully connected layers of 1024 nodes followed by batch normalization .

the convnet contained a cascade of three 2d convolutional , max-pooling connected to a fully connected layer .

we pre-train the transform network using the whole set of the celeba dataset d with about 200,000 face images .

we evaluate our method using the celeba dataset , which consists of 40 facial attribute labels and 202,599 images .

generalizing this argument gives the following easy theorem .

we summarize this result in the following theorem .

assume that the configuration space is a lie group g and denote the local coordinates in g by g .

more generally however , the configuration space is the smooth riemann surface σ .

centralized channel assignment and routing algorithms for multi-channel wireless mesh networks .

joint routing and channel assignment in multi-radio wireless mesh networks .

this approach is also considered in for multipleinput single output and mimo scenarios , respectively , with the assumption that one user is entrusted and the other is the potential eavesdropper .

this approach is also considered in for multiple-input single output and mimo scenarios , respectively , in a two-user setting , with the assumption that one user is entrusted and the other is the potential eavesdropper .

at least one of these jets must be consistent with the decay of a heavy-flavour hadron , identified by the combined secondary vertex b-tagging algorithm .

at least one of these jets must be consistent with containing the decay of a heavy-flavor hadron , as identified using the medium operating point of the combined secondary vertex b tagging algorithm .

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

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 .

convolutional neural networks have surpassed many traditional machine learning approaches in solving several computer vision tasks such as classification and others .

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

a plaquette is a closed loop consists of 4 different points .

the plaquette is a piece of a curved manifold .

this is particularly relevant at high transverse momenta , where ew corrections are strongly enhanced by logarithmic contributions of sudakov type , which can reach several tens of percent at the tev scale .

moreover , ew corrections are especially relevant at the tev scale , where large logarithms of sudakov type can lead to nlo ew effects of tens of percent .

its phase space is a cylinder to a mixed regime with a large chaotic domain .

the phase space a consist of the solutions of eq .

overlaid is a band representing the maximal variation of the result under various spinalignment scenarios .

overlaid is a grid of the loci of a simple absorbed power law model as γ and nh vary .

deep learning techniques have recently enabled researchers to successfully tackle low-level perception problems in a supervised learning fashion .

most recently , the field of deep learning or deep neural networks has advanced rapidly leading to breakthroughs in both high-level and low-level vision problems .

glagolev vv , gulamov kg , kratenko myu et .

glagolev vv , gulamov kg , lipin vd et .

convolutional neural networks have achieved remarkable impact in many machine learning applications , including computer vision , natural language processing and reinforcement learning .

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

arenas et al detected aibo robot and humanoid robots using the cascade of boosted classifiers , which is suitable for real-time applications .

arenas et al proposed a real-time capable aibo and humanoid robot detector using a cascade of boosted classifiers .

the mapping of the ab initio data onto the effective spin hamiltonian is carried out following the procedure described in refs .

mapping of the ab initio data onto an effective spin hamiltonian is carried out following the procedure earlier used in refs .

deep neural networks have exhibited great performance in computer vision tasks in recent years .

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

chrobak and sgall showed that any memoryless randomized algorithm has unbounded competitive ratio .

koutsoupias and taylor shows that any memoryless randomized algorithm has unbounded competitive ratio in this case .

indeed , as we will show in section v , string-net condensation naturally gives rise to both gauge interactions and fermi statistics .

however , we know that string-net condensation quite generally describes all lattice gauge theories with or without emergent fermi statistics .

as srcnn is less effective in the detail estimation , kim et al propose the residual learning algorithm based on a deeper network .

kim et al addressed certain limitations of srcnn with a very deep super-resolution network which can be efficiently trained relying on fast residual learning .

these slopes and is a monotonically decreasing function of γ .

their slopes are called the d regular slopes .

here we employ the power method in combination with the constrained sss samplings .

note that only one sampling is enough in the constrained sss method .

let us also insist that spacetime is a manifold .

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

deep neural networks have achieved state-of-the-art performance in many application areas , such as computer vision and natural language processing .

deep neural networks are powerful machine learning systems , which have been demonstrated in a variety of tasks including image classification among others .

there has been extensive discussion of the structure of fermion masses in f-theory .

recently there has been much interest in the possibility that the fermion mass structure might emerge from f-theory .

we extract visual features from the person-centric images using the alexnet convolutional network .

to evaluate the proposed toolflow , we target image classification using pretrained models on the imagenet dataset .

qubit a is the control bit for qutrit c and qubit b is the control bit for qutrit d .

qubit a is the control bit for the controlledu 2 gate , qubit b is the control bit for the controlled-u gate , and qubit c is the be the eigenstates of u with corresponding target bit for both .

electronic exchange correlation is treated under the generalised gradient approximation using perdew-burke-ernzerhof functional .

exchange and correlations are considered in the generalized gradient approximation , following the perdew-burke-ernzerhof parametrization scheme .

besides , song et al introduce the binary segmentation masks to construct synthetic rgb-mask pairs as inputs , then they design a mask-guided contrastive attention model to learn features separately from the body and background regions .

song et al introduced the binary segmentation masks to construct synthetic rgb-mask pairs as inputs , as well as a mask-guided contrastive attention model to learn features separately from body and background regions .

in this case φ is called an isomorphism of g onto h .

then this isomorphism is the identity map .

this can be achieved by the use of cmos compatible resistive crossbar memory based on ag-si memristors .

such devices can be integrated into metallic crossbars to obtain high density resistive crossbar memory .

since gravity is the universal force which couples to all energy sources , the decay of the inflaton is necessarily 3 accompanied by non-thermal emission of kk gravitons with masses comparable to mφ .

since gravity is a gauge theory , one has to take into account the complications due to the gauge fixing and ghost 19 terms .

two classes of wave packets with an arbitrarily given degree of rigidity are presented .

two classes of wave packets with an arbitrarily given degree of rigidity are given explicitly .

collell et al introduce a multi-modal recurrent neural network to generate image descriptions .

karpathy et al use deep learning to produce descriptions of images , which compete with human generated labels .

so corresponding to every two tilings of rwhere the leftmost five columns match the pattern in figure 11 , we get one tiling where the leftmost four columns match the pattern in figure 11 .

so , corresponding to each tiling of r , where the leftmost five columns match the pattern in figure 11 , we get a tiling where the leftmost four columns match the pattern in figure 11 .

statistical learning of a language model aims to approximate the probability distribution on the set of expressions in the language .

a goal of language modeling is to learn the joint probability function of sequences of words in a language .

deep neural networks have achieved tremendous success in recent years , due to the ability of these models to achieve state-of-the-art performances .

the accuracy of deep convolutional neural networks for visual categorization has advanced substantially from 2012 levels to current state-of-the-art cnns like resnet .

the surf features are shallow features extracted and quantized into an 800-bin histogram using a codebook computed with k-means on a subset of images from amazon .

these sub-datasets are based on surf features have been made by , which are extracted and quantized into an 800-bin histogram with codebooks computed with k-means on a subset of images from amazon .

the star detector consists of many detector subsystems in a large solenoidal magnet with the time projection chamber located at 18 m from the center of the tpc .

the star detector consists of a 4 2 m long cylindrical time projection chamber at 18m from the interaction point are sensitive to the neutral remnants of nuclear breakup .

originally introduced to explain the absence of charge-parity violation in strong interactions , the axion is one of the best motivated cold dark matter candidates .

the axion , a nambu-goldstone boson , is a solution to the strong cp problem of qcd and a plausible cold dark matter candidate .

in this paper , afm uses long short-term memory -recurrent neural networks .

this model is first built as a 4 layer long short-term memory -recurrent neural networks .

the data were reduced using the miriad software package .

the data underwent a standard data reduction with the miriad software package .

a g-action on x is called smart if 0 is an isomorphism .

the isomorphism is the natural , forgetful mapping sending a kasparov cycle to a kk ban-cycle .

we could say that the tf-g regime should exhibit the superfluid properties more prominently than the g-regime .

we find that the tf-g regime can exhibit the superfluid properties more prominently than the g-regime .

consider the entropy of two system copies .

consider the entropy production density of radiative transfer .

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

in phase space there is a curve that attracts most of the trajectories .

evolutionary game theory has been introduced as a framework to study the processes of selection of genes or behaviors in biological and social systems .

evolutionary game theory is widely applied to study the maintenance of cooperation among the selfish individuals .

now we proceed on to define the cauchy elements in biquasi loops .

now we proceed on to define non-associative binear-rings .

let us check criteria is the only relevant length scale .

the criteria is the dominant part of the scalar potential during inflation is independent of the field value .

deep learning has shown its effectiveness in many computer vision tasks , such as object detection .

object recognition in large-scale image datasets has achieved impressive performance with deep convolutional neural networks .

now , we introduce the following outer bound for the capacity region of the degraded discrete memoryless multi-receiver wiretap channel with public and confidential messages .

finally , we provide an inner bound for the capacity region of the general , not necessarily degraded , gaussian mimo multi-receiver wiretap channel .

latent dirichlet allocation is a topic modeling technique for textual data .

latent dirichlet allocation is a generative probabilistic model for collections of a corpus .

now we consider the factorization of the general transfer matrix .

now we are going to consider explicit formulae for the action of these operators on polynomials .

the number of the condensed counterion nc on each plate is determined by minimizing the total free energy including fluctuation contributions .

the number of condensed counterions is determined self-consistently , by minimizing the total free energy which includes fluctuation contributions .

in this section , we introduce how scalable estimation of mutual information is performed in terms of practical scenarios via mutual information neural estimation and the deep infomax described below .

in this section , we describe the neural network proposed in for estimating mutual information based on an alternative representations of kl-divergence .

aeppli , jw lynn , pg pagliuso , jl sarrao , mf hundley , jd thompson , and z .

nicklas , no moreno , jd thompson , mf hundley , jl sarrao , and z .

for this it suffices to prove that it is a closed embedding .

so it suffices to prove that s is a state space , and convex .

however , nonlinearities from the ac power flow equations result in the ac-opf problem being nonconvex and generally np-hard .

coupling this with nonconvex ac powerflow constraints leads to a mixedinteger nonlinear programming problem that is np-hard .

if neglected , these two reactions would have the highest contribution to the error .

this means that if any of these four reactions are neglected , they would have the highest contribution to the error .

illustrate the above definition by an example .

we now illustrate this by the following example .

for the numerical integration , we provide a simple interface to integrators from the cuba library .

for multidimensional numerical integration we use the cuba library .

an alternative approach may consist in using cubic splines to approximate each set of time series but this requires the setting of knots which may a combinatory complex task .

an alternative approach in this curve clustering context may consist in using cubic splines to model each class of curves james and sugar but this requires the setting of knots a priori .

the observed smc depletions can be modeled with the scaling law if the smc abundance ratios are slightly non solar .

in conclusion , it is not possible to model the smc depletions if the smc abundances are strictly solar .

quantum statistical mechanics and galois theory .

chaotic behaviour and the einstein equations .

the total number of species in the food web denoted by s .

the fraction of omnivorous species in the food web denoted by o .

infogan learned disentangled latent space unsupervisedly by adding regularizers to the generator to maximize the mutual information .

under the unsupervised setting , infogan learned disentangled representation by maximizing the mutual information between latent code and data observation .

deep neural networks have been widely used in many artificial intelligence applications including computer vision .

deep neural networks have been successfully applied to many machine learning and statistical inference problems including speech recognition , natural language processing .

parameterized complexity of constraint satisfaction problems .

the approximability of constraint satisfaction problems .

the quantum key distribution is one of the most mature quantum cryptography technologies , which can provide information-theoretical provable security together with the one-time pad method .

among the applications of the quantum network , quantum key distribution is one of the first technology in quantum information science to produce practical applications .

for this task , we employ inceptionv3 network architecture , with pretrained weights from imagenet for initialization .

we use the output of the final global average pooling layer of inception-v3 deep learning network for the purpose .

similarly , grosse et al tested a suite of feature reduction methods specifically in the malware domain .

grosse et al proposed to use the gradient based approach to generate adversarial android malware examples .

it implies that here not only spontaneous but also stimulated emission of radiation comparable with spontaneous emission occurs .

it implies that now not only spontaneous but also stimulated emission of radiation comparable with spontaneous emission occurs .

in the sequel , f denotes a convex monotone homogeneous map that has an eigenvector .

in the sequel we shall further assume that f is a c 2 convex function , and under this assumption we shall show that such functions are precisely those decomposing as per eq .

here we note that spin reversal symmetry has not been considered explicitly in previous studies of level statistics for various quantum spin chains .

we may therefore expect that the rmt analysis of the xxz spin chains is important in discussing level statistics for other quantum systems that have some connection to an integrable system .

we first compare with a traditional regionlet method when training using small size dataset .

we first compare with traditional regionlet method when training using small size dataset .

now we give the definition of non-associative biseminear-rings .

now we proceed on to define the concept of bisemigroup birings .

other string coordinates remain unchanged .

the string coordinates and momenta remain unchanged .

now we proceed on to define smarandache non-associative near-rings .

now we proceed on to define smarandache pseudo left ideals .

for the symbol tr denotes integral constant electromagnetic fields , the integrand in explicitly .

here and below , the symbol tr denotes the contraction with respect to all repeated indices , which will not be shown explicitly .