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Author Information
Tong Che (MILA)
Ruixiang ZHANG (Mila/UdeM)
Jascha Sohl-Dickstein (Google Brain)
Hugo Larochelle (Google Brain)
Liam Paull (Université de Montréal)
Yuan Cao (Google Brain)
Yoshua Bengio (Mila / U. Montreal)
Yoshua Bengio is Full Professor in the computer science and operations research department at U. Montreal, scientific director and founder of Mila and of IVADO, Turing Award 2018 recipient, Canada Research Chair in Statistical Learning Algorithms, as well as a Canada AI CIFAR Chair. He pioneered deep learning and has been getting the most citations per day in 2018 among all computer scientists, worldwide. He is an officer of the Order of Canada, member of the Royal Society of Canada, was awarded the Killam Prize, the Marie-Victorin Prize and the Radio-Canada Scientist of the year in 2017, and he is a member of the NeurIPS advisory board and co-founder of the ICLR conference, as well as program director of the CIFAR program on Learning in Machines and Brains. His goal is to contribute to uncover the principles giving rise to intelligence through learning, as well as favour the development of AI for the benefit of all.
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2020 Spotlight: Finite Versus Infinite Neural Networks: an Empirical Study »
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2019 Workshop: Retrospectives: A Venue for Self-Reflection in ML Research »
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2019 Poster: Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent »
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2019 Poster: Unsupervised State Representation Learning in Atari »
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2019 Poster: Variational Temporal Abstraction »
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2019 Poster: Gradient based sample selection for online continual learning »
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2019 Poster: MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis »
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Yoshua Bengio -
2019 Poster: On Adversarial Mixup Resynthesis »
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2019 Poster: Invertible Convolutional Flow »
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2019 Spotlight: Invertible Convolutional Flow »
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2019 Poster: Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input »
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2019 Poster: Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics »
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2019 Oral: Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input »
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2018 Workshop: AI for social good »
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2018 Poster: Image-to-image translation for cross-domain disentanglement »
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2018 Poster: MetaGAN: An Adversarial Approach to Few-Shot Learning »
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2018 Poster: PCA of high dimensional random walks with comparison to neural network training »
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2018 Poster: Bayesian Model-Agnostic Meta-Learning »
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2018 Poster: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding »
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2018 Spotlight: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding »
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2018 Spotlight: Bayesian Model-Agnostic Meta-Learning »
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2018 Poster: Adversarial Examples that Fool both Computer Vision and Time-Limited Humans »
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2018 Poster: Dendritic cortical microcircuits approximate the backpropagation algorithm »
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2018 Oral: Dendritic cortical microcircuits approximate the backpropagation algorithm »
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2017 Poster: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models »
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2017 Poster: Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net »
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2017 Oral: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models »
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2017 Demonstration: A Deep Reinforcement Learning Chatbot »
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2017 Poster: GibbsNet: Iterative Adversarial Inference for Deep Graphical Models »
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2017 Poster: Plan, Attend, Generate: Planning for Sequence-to-Sequence Models »
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2017 Poster: SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability »
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2017 Poster: Z-Forcing: Training Stochastic Recurrent Networks »
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2017 Poster: A Meta-Learning Perspective on Cold-Start Recommendations for Items »
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2016 Workshop: Brains and Bits: Neuroscience meets Machine Learning »
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2016 Symposium: Deep Learning Symposium »
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2016 Poster: Architectural Complexity Measures of Recurrent Neural Networks »
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2016 Poster: Professor Forcing: A New Algorithm for Training Recurrent Networks »
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2016 Poster: Exponential expressivity in deep neural networks through transient chaos »
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2016 Poster: On Multiplicative Integration with Recurrent Neural Networks »
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2016 Poster: Binarized Neural Networks »
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2015 Workshop: Statistical Methods for Understanding Neural Systems »
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2015 Symposium: Deep Learning Symposium »
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2015 Poster: Attention-Based Models for Speech Recognition »
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2015 Poster: Equilibrated adaptive learning rates for non-convex optimization »
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2015 Poster: Deep Knowledge Tracing »
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2015 Poster: A Recurrent Latent Variable Model for Sequential Data »
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2015 Poster: BinaryConnect: Training Deep Neural Networks with binary weights during propagations »
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2015 Tutorial: Deep Learning »
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2014 Workshop: Second Workshop on Transfer and Multi-Task Learning: Theory meets Practice »
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2014 Workshop: Deep Learning and Representation Learning »
Andrew Y Ng · Yoshua Bengio · Adam Coates · Roland Memisevic · Sharanyan Chetlur · Geoffrey E Hinton · Shamim Nemati · Bryan Catanzaro · Surya Ganguli · Herbert Jaeger · Phil Blunsom · Leon Bottou · Volodymyr Mnih · Chen-Yu Lee · Rich M Schwartz -
2014 Workshop: OPT2014: Optimization for Machine Learning »
Zaid Harchaoui · Suvrit Sra · Alekh Agarwal · Martin Jaggi · Miro Dudik · Aaditya Ramdas · Jean Lasserre · Yoshua Bengio · Amir Beck -
2014 Poster: How transferable are features in deep neural networks? »
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2014 Poster: Identifying and attacking the saddle point problem in high-dimensional non-convex optimization »
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2014 Poster: Generative Adversarial Nets »
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2014 Poster: On the Number of Linear Regions of Deep Neural Networks »
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2014 Demonstration: Neural Machine Translation »
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2014 Oral: How transferable are features in deep neural networks? »
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2014 Session: Oral Session 3 »
Hugo Larochelle -
2014 Poster: An Autoencoder Approach to Learning Bilingual Word Representations »
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2014 Poster: Iterative Neural Autoregressive Distribution Estimator NADE-k »
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2013 Workshop: Deep Learning »
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2013 Workshop: Output Representation Learning »
Yuhong Guo · Dale Schuurmans · Richard Zemel · Samy Bengio · Yoshua Bengio · Li Deng · Dan Roth · Kilian Q Weinberger · Jason Weston · Kihyuk Sohn · Florent Perronnin · Gabriel Synnaeve · Pablo R Strasser · julien audiffren · Carlo Ciliberto · Dan Goldwasser -
2013 Session: Spotlight Session 10 »
Hugo Larochelle -
2013 Session: Spotlight Session 9 »
Hugo Larochelle -
2013 Session: Spotlight Session 8 »
Hugo Larochelle -
2013 Session: Spotlight Session 7 »
Hugo Larochelle -
2013 Session: Spotlight Session 6 »
Hugo Larochelle -
2013 Session: Spotlight Session 5 »
Hugo Larochelle -
2013 Poster: Multi-Prediction Deep Boltzmann Machines »
Ian Goodfellow · Mehdi Mirza · Aaron Courville · Yoshua Bengio -
2013 Poster: Generalized Denoising Auto-Encoders as Generative Models »
Yoshua Bengio · Li Yao · Guillaume Alain · Pascal Vincent -
2013 Poster: Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs »
Yann Dauphin · Yoshua Bengio -
2013 Poster: RNADE: The real-valued neural autoregressive density-estimator »
Benigno Uria · Iain Murray · Hugo Larochelle -
2013 Session: Spotlight Session 4 »
Hugo Larochelle -
2013 Session: Spotlight Session 3 »
Hugo Larochelle -
2013 Session: Spotlight Session 2 »
Hugo Larochelle -
2013 Session: Spotlight Session 1 »
Hugo Larochelle -
2012 Workshop: Deep Learning and Unsupervised Feature Learning »
Yoshua Bengio · James Bergstra · Quoc V. Le -
2012 Poster: A Neural Autoregressive Topic Model »
Hugo Larochelle · Stanislas Lauly -
2012 Poster: Training sparse natural image models with a fast Gibbs sampler of an extended state space »
Lucas Theis · Jascha Sohl-Dickstein · Matthias Bethge -
2012 Poster: Practical Bayesian Optimization of Machine Learning Algorithms »
Jasper Snoek · Hugo Larochelle · Ryan Adams -
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2011 Oral: The Manifold Tangent Classifier »
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