Sequential decision modeling in uncertain conditions

Improving predictive behavior under distributional shift

Differentiable best response shaping

Emergence of language-like latents in deep neural networks

Stabilizing Q-Learning for continuous control

AI alignment and generalization in deep learning

Controllable music performance synthesis via hierarchical modelling

Advances in generative models for dynamic scenes

On iterated learning for task-oriented dialogue

Syntactic inductive biases for deep learning methods

On discovering and learning structure under limited supervision

Continuous coordination as a realistic scenario for lifelong learning

Towards deep unsupervised inverse graphics

Data-efficient reinforcement learning with self-predictive representations

On improving variational inference with low-variance multi-sample estimators

Estimation neuronale de l'information mutuelle.

Emerging communication between competitive agents

Deep learning and reinforcement learning methods for grounded goal-oriented dialogue

Representation learning in unsupervised domain translation

Representation learning for dialogue systems

Advances in deep learning with limited supervision and computational resources

Towards learning sentence representation with self-supervision

No Press Diplomacy

Latent variable language models

Learning visual representations with neural networks for video captioning and image generation

Sequence to sequence learning and its speech applications

Generative models : a critical review

Representation Learning for Visual Data

Exploring Attention Based Model for Captioning Images

Deep Learning for Video Modelling

Generative models for natural images

Towards deep semi supervised learning

Speech synthesis using recurrent neural networks

Influencing the Properties of Latent Spaces

Sequential modeling, generative recurrent neural networks, and their applications to audio

Deep learning of representations and its application to computer vision

Distributed conditional computation

Leveraging noisy side information for disentangling of factors of variation in a supervised setting

Promoting systematic generalization in vision-and-language foundation models

Canada Research Chair in Learning representations that generalize systematically

Nomination à titre de conseiller scientifique

Extending the Frontiers of Deep Generative Modelling

Mastering Multi-modal Decision-making with World-Models

Hierarchical Context Retrieval for LLM Question Answering

High frequency measurement generation model from low frequency features››

ML for Action Detection in Movies for Haptic Effects Generation

"Personal Assistant for Blind people”

Software infrastructure for Deep Learning

Generation model optimization

Fellow, CCAI Chair, CIFAR program in Learning in Machines & Brains

Physics-inspired Deep Generative Modeling and New Physics Search for High Energy Physics

Apogée Canada fonds d'excellence en recherche / Bourse d'excellence IVADO au doctorat Lluis E. Castrejon Subira

Visual-haptic Representation for Zero-shot Learning

Unsupervised Learning of 3D Scenes from Images using a View-based Representation

Support research related to the CIFAR program in Learning in Machines & Brains_Fellow

Programme de stages - IVADO - Eugene Belilovsky /Towards Learning Language Based Navigation in Visually Rich 3-D Environments

Fellow of the CIFAR LMB Program / CIFAR program Learning in Machine & Brains

Software infrastructure for Deep Learning

Unsupervised Learning of 3D Scenes from Images using a View-based Representation

Apprentissage non-supervisé d'architectures profondes pour le changement d'expressions faciales

CIFAR// Fellow // Research Support and Teaching Release // Learning in Machines & Brains

Interative Grounded Language Understanding (IGLU)

PROBABILISTIC MODELS FOR AUTOMATIC EQUIVARIANT FEATURE DISCOVERY

Highperformance computing environment to leverage deep learning technology for large biomedical and neuroimaging data

Deep Learning for Cognitive Computing

Interactive Grounded Language Understanding (IGLU)

DEVELOPPEMENT D'UN SYSTÈME ROBUSTE DE RECONNAISSANCE D'ACTIVITES HUMAINES UTILISANT DES FILMS ET LEUR TEXTE DESCRIPTIF

RESEARCH ON SCALING UP DEEP LEARNING

L'APPRENTISSAGE PROFOND DES IMAGES ET DU LANGAGE NATUREL

CIFAR//Fellow//Research Support

ADIABATIC QUANTUM COMPUTING FOR DEEP LEARNING WITH BOLTZMANN MACHINES

LARGE-SCALE DEEP LEARNING FOR CONTENT-BASED RECOMMENDATION SYSTEMS