14.5k citations · 90.1k across the 347 of their papers we have counts for
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Dendritic error backpropagation in deep cortical microcircuits
João Sacramento, Rui Ponte Costa, Yoshua Bengio +1
Animal behaviour depends on learning to associate sensory stimuli with the desired motor command. Understanding how the brain orchestrates the necessary synaptic modifications acro…
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Alex Lamb, Devon Hjelm, Yaroslav Ganin +3
Directed latent variable models that formulate the joint distribution as have the advantage of fast and exact sampling. However, these models have the w…
ObamaNet: Photo-realistic lip-sync from text
Rithesh Kumar, Jose Sotelo, Kundan Kumar +2
We present ObamaNet, the first architecture that generates both audio and synchronized photo-realistic lip-sync videos from any new text. Contrary to other published lip-sync appro…
Measuring the tendency of CNNs to Learn Surface Statistical Regularities
Jason Jo, Yoshua Bengio
Deep CNNs are known to exhibit the following peculiarity: on the one hand they generalize extremely well to a test set, while on the other hand they are extremely sensitive to so-c…
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
Francis Dutil, Caglar Gulcehre, Adam Trischler +1
We investigate the integration of a planning mechanism into sequence-to-sequence models using attention. We develop a model which can plan ahead in the future when it computes its…
Z-Forcing: Training Stochastic Recurrent Networks
Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté +2
Many efforts have been devoted to training generative latent variable models with autoregressive decoders, such as recurrent neural networks (RNN). Stochastic recurrent models have…