← Authors

Aaron C. Courville

26 papers · 2007–2023 · 1 conference · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (53) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (16) 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (26) πŸ”₯ Unstoppable (9) πŸ’Ž Century Club (26) ⚑ Prolific Year (6) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (128)

Conferences

NIPS (26)

Top co-authors

Yoshua Bengio (8) Max Schwarzer (3) Chin-Wei Huang (3) Samuel Lavoie (2) Alessandro Sordoni (2) Marc Bellemare (2) Pablo Samuel Castro (2) Shawn Tan (2) Florian Strub (2) Alex M Lamb (2)

Keywords

variational inference (4) reinforcement learning (3) generative adversarial network (3) generative model (3) score matching (2) latent variable model (2) self-supervised learning (2) variational autoencoder (2) representation learning (2) likelihood estimation (2) latent space (2) recurrent neural network (2) transfer learning (1) nonparametric bayesian (1) image generation (1) contrastive learning (1) deep reinforcement learning (1) bayesian nonparametrics (1) feature learning (1) visual question answering (1)

Papers

Double Gumbel Q-Learning NIPS 2023
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings NIPS 2023
Group Robust Classification Without Any Group Information NIPS 2023
Versatile Energy-Based Probabilistic Models for High Energy Physics NIPS 2023
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets NIPS 2023
Language Model Alignment with Elastic Reset NIPS 2023
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress NIPS 2022
Riemannian Diffusion Models NIPS 2022
Pretraining Representations for Data-Efficient Reinforcement Learning NIPS 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice NIPS 2021
A Variational Perspective on Diffusion-Based Generative Models and Score Matching NIPS 2021
Gradient Starvation: A Learning Proclivity in Neural Networks NIPS 2021
Unsupervised Learning of Dense Visual Representations NIPS 2020
Ordered Memory NIPS 2019
No-Press Diplomacy: Modeling Multi-Agent Gameplay NIPS 2019
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis NIPS 2019
Improving Explorability in Variational Inference with Annealed Variational Objectives NIPS 2018
Towards Text Generation with Adversarially Learned Neural Outlines NIPS 2018
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models NIPS 2017
Improved Training of Wasserstein GANs NIPS 2017
Modulating early visual processing by language NIPS 2017
Professor Forcing: A New Algorithm for Training Recurrent Networks NIPS 2016
A Recurrent Latent Variable Model for Sequential Data NIPS 2015
On Tracking The Partition Function NIPS 2011
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism NIPS 2009
The rat as particle filter NIPS 2007