440 citations · 947 across the 43 of their papers we have counts for
4 papers · 1 filter
Hierarchical Adversarially Learned Inference
Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro +3
We propose a novel hierarchical generative model with a simple Markovian structure and a corresponding inference model. Both the generative and inference model are trained using th…
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni +2
Learning inter-domain mappings from unpaired data can improve performance in structured prediction tasks, such as image segmentation, by reducing the need for paired data. CycleGAN…
A Deep Reinforcement Learning Chatbot (Short Version)
Iulian V. Serban, Chinnadhurai Sankar, Mathieu Germain +15
We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition. MILABOT is capa…
MINE: Mutual Information Neural Estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar +4
We argue that the estimation of mutual information between high dimensional continuous random variables can be achieved by gradient descent over neural networks. We present a Mutua…