• Aucun résultat trouvé

[PDF] Top 20 Entropy and mutual information in models of deep neural networks

Has 10000 "Entropy and mutual information in models of deep neural networks" found on our website. Below are the top 20 most common "Entropy and mutual information in models of deep neural networks".

Entropy and mutual information in models of deep neural networks

Entropy and mutual information in models of deep neural networks

... approximation of the tanh, hardtanh(x) = −1 for x<−1, x for −1<x<1, and 1 for x>1, for which the integrals in the replica formula can be evaluated faster than for the ...tanh. In ... Voir le document complet

66

On Recurrent and Deep Neural Networks

On Recurrent and Deep Neural Networks

... order information to natural gradient, does perform better than natural gradient (and it seems to outperform, in terms of time, SGD as ...well). In particular, NatCG-L is doing ... Voir le document complet

267

Deep neural networks for direct, featureless learning through observation: the case of two-dimensional spin models

Deep neural networks for direct, featureless learning through observation: the case of two-dimensional spin models

... space of the 4 × 4 Ising ...density of states. to the number of example configurations provided during ...20% of configuration space (some energy classes are over-sampled to fill the ... Voir le document complet

11

Adaptive structured noise injection for shallow and deep neural networks

Adaptive structured noise injection for shallow and deep neural networks

... success of deep neural networks (DNN) for many machine learning tasks such as image classification and object recognition (Krizhevsky et ...representations of the data, able to ... Voir le document complet

17

Deep neural networks for natural language processing and its acceleration

Deep neural networks for natural language processing and its acceleration

... performance of our model when trained with ground- truth trees as ...[159] and LSTM, especially for long ...sequence and does not encode sequences ...other models, especially in the ... Voir le document complet

140

Mean-field Langevin System, Optimal Control and Deep Neural Networks

Mean-field Langevin System, Optimal Control and Deep Neural Networks

... space of probability measures and the regularizer Ent is the relative entropy with respect to the Lebesgue measure, see ...law of the process (1.4) converges to its invariant measure. As ... Voir le document complet

25

Deep neural networks for choice analysis

Deep neural networks for choice analysis

... change of tolls or subsidies [118, 53]. VOT, as one impor- tant instance of MRS, can be used to measure the monetary gain of saved time after the improvement of a transportation system ... Voir le document complet

128

New Paradigm in Speech Recognition: Deep Neural Networks

New Paradigm in Speech Recognition: Deep Neural Networks

... GMM-HMM and DNN-HMM KATS systems. From 2012, deep learning has shown excellent results in many domains: image recognition, speech recognition, language modelling, parsing, information ... Voir le document complet

8

2020 — Modeling information flow through deep convolutional neural networks

2020 — Modeling information flow through deep convolutional neural networks

... complexity and/or increasing accuracy of the specific task, ...accuracy of specific task using efficient transfer learning with the new method for feature selection based on information ...number ... Voir le document complet

180

Applications of complex numbers to deep neural networks

Applications of complex numbers to deep neural networks

... phase information. Results are reported in Table ...phase information encoding is presented in section ...Transcription In this section we present results for the automatic music ... Voir le document complet

57

Stabilizing and Enhancing Learning for Deep Complex and Real Neural Networks

Stabilizing and Enhancing Learning for Deep Complex and Real Neural Networks

... use of deep learning techniques has also gained growing interest in recent ...category of methods. Huang et al. (2014a) were the earliest to use a deep learning approach to modeling ... Voir le document complet

146

Auto-Encoders, Distributed Training and Information Representation in Deep Neural Networks

Auto-Encoders, Distributed Training and Information Representation in Deep Neural Networks

... Stochastic Networks We introduce a novel training principle for generative probabilistic models that is an alternative to maximum ...(DAE) and is based on learning the transition operator of a ... Voir le document complet

191

On the Expressive Power of Deep Fully Circulant Neural Networks

On the Expressive Power of Deep Fully Circulant Neural Networks

... class of compact neural networks: deep networks in which all weight matrices are either diag- onal or circulant ...such networks with a large number of layers had ... Voir le document complet

14

Multichannel Music Separation with Deep Neural Networks

Multichannel Music Separation with Deep Neural Networks

... problem of multichannel music ...using deep neural networks and combined with spatial covariance matrices to encode the source spatial ...estimated in an iterative ... Voir le document complet

6

Probabilistic Robustness Estimates for Deep Neural Networks

Probabilistic Robustness Estimates for Deep Neural Networks

... bound of the Lipschitz constant of the network has also been proposed as regularization that pro- motes ...ularity of the network and acts also as an overall control on the contraction power ... Voir le document complet

10

Deep neural networks for audio scene recognition

Deep neural networks for audio scene recognition

... Influence of the size of the DNN In this paragraph, we consider a fixed number of 15 input frames (so the size of the input layer of our DNN is 15× 30 = 450) and we ... Voir le document complet

6

Mutual information, Fisher information and population coding

Mutual information, Fisher information and population coding

... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ... Voir le document complet

30

In-Memory and Error-Immune Differential RRAM Implementation of Binarized Deep Neural Networks

In-Memory and Error-Immune Differential RRAM Implementation of Binarized Deep Neural Networks

... NTRODUCTION Deep neural networks are currently the most widely investigated architecture in Artificial Intelligence (AI) systems, with incredible achievements in image recognition, ... Voir le document complet

5

Unsupervised Layer-Wise Model Selection in Deep Neural Networks

Unsupervised Layer-Wise Model Selection in Deep Neural Networks

... Abstract. Deep Neural Networks (DNN) propose a new and ef- ficient ML architecture based on the layer-wise building of several representation ...number of neurons in each ... Voir le document complet

7

Clinical event prediction and understanding with deep neural networks

Clinical event prediction and understanding with deep neural networks

... In addition, we compare these representations along with both long short-term memory networks (LSTM) and convolutional neural networks (CNN) for prediction of five i[r] ... Voir le document complet

56

Show all 10000 documents...