Aaron C. Courville

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

Achievements

+9 more ↓

🏃 Academic Marathon (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (13)

🐝 Cross-Pollinator (13) 🏃 Academic Marathon (16) 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (26) 🔥 Unstoppable (9) 💎 Century Club (26) ⚡ Prolific Year (6) 📈 Trend Setter 🗃️ 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