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about
P112
P185
P1889
Theano: A Python framework for fast computation of mathematical expressionsDeep LearningGenerative Adversarial NetsDeep learningRepresentation Learning: A Review and New PerspectivesChar2Wav: End-to-End Speech SynthesisEfficient Non-Parametric Function Induction in Semi-Supervised LearningShow, Attend and Tell: Neural Image Caption Generation with Visual AttentionDeep Generative Stochastic Networks Trainable by BackpropA Neural Probabilistic Language ModelEquilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation.Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine TranslationNeural Machine Translation by Jointly Learning to Align and TranslateGradient-based learning applied to document recognitionThe Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions.Equilibrated adaptive learning rates for non-convex optimizationLearning structured embeddings of knowledge basesA neural probabilistic language modelOn the challenge of learning complex functions.Representation learning: a review and new perspectivesOn the Properties of Neural Machine Translation: Encoder-Decoder ApproachesChallenges in representation learning: a report on three machine learning contests.Brain tumor segmentation with Deep Neural Networks.The Consciousness PriorCurriculum learningTheano: a CPU and GPU math compiler in PythonGeneralization in Deep LearningAlternative time representation in dopamine models.Nonlocal estimation of manifold structure.Selective small molecule peptidomimetic ligands of TrkC and TrkA receptors afford discrete or complete neurotrophic activities.Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent NetGibbsNet: Iterative Adversarial Inference for Deep Graphical ModelsPlan, Attend, Generate: Planning for Sequence-to-Sequence ModelsZ-Forcing: Training Stochastic Recurrent NetworksConditioning and time representation in long short-term memory networks.Use machine learning to find energy materials.Collaborative filtering on a family of biological targets.Boosting neural networks.Architectural Complexity Measures of Recurrent Neural NetworksOn Multiplicative Integration with Recurrent Neural Networks
P50
description
Canadees professor
@nl
Canadian computer scientist
@en
datalog
@da
informaticien canadien
@fr
kanadischer Informatiker
@de
ríomheolaí Ceanadach
@ga
מדען מחשב קנדי
@he
加拿大计算机科学家
@zh
加拿大计算机科学家
@zh-hans
name
Yoshua Bengio
@af
Yoshua Bengio
@ast
Yoshua Bengio
@br
Yoshua Bengio
@ca
Yoshua Bengio
@co
Yoshua Bengio
@da
Yoshua Bengio
@de
Yoshua Bengio
@dsb
Yoshua Bengio
@en
Yoshua Bengio
@es
type
label
Yoshua Bengio
@af
Yoshua Bengio
@ast
Yoshua Bengio
@br
Yoshua Bengio
@ca
Yoshua Bengio
@co
Yoshua Bengio
@da
Yoshua Bengio
@de
Yoshua Bengio
@dsb
Yoshua Bengio
@en
Yoshua Bengio
@es
altLabel
Бенжио, Йошуа
@ru
prefLabel
Yoshua Bengio
@af
Yoshua Bengio
@ast
Yoshua Bengio
@br
Yoshua Bengio
@ca
Yoshua Bengio
@co
Yoshua Bengio
@da
Yoshua Bengio
@de
Yoshua Bengio
@dsb
Yoshua Bengio
@en
Yoshua Bengio
@es