← Authors

Theophane Weber

23 papers · 2015–2023 · 4 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (8) 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (13) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (31) 🌍 Conference Polyglot (4) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (85) πŸ’Ž Century Club (23) πŸ”₯ Unstoppable (9)

Conferences

NIPS (8) ICML (7) ICLR (6) AISTATS (2)

Top co-authors

Arthur Guez (10) Nicolas Heess (9) Lars Buesing (8) David Silver (6) Fabio Viola (4) Timothy Lillicrap (4) Sébastien Racanière (3) Rémi Munos (3) Razvan Pascanu (3) Daan Wierstra (3)

Keywords

reinforcement learning (5) value function (5) variance reduction (4) neural network (4) credit assignment (3) model-free reinforcement learning (3) policy gradient (3) probabilistic inference (2) environment model (2) deep reinforcement learning (2) offline reinforcement learning (2) experience retrieval (2) planning algorithm (2) model learning (2) tree search (2) model-based reinforcement learning (2) stochastic computation graph (2) monte carlo tree search (2) visual observation (1) scene understanding (1)

Papers

Quantile Credit Assignment ICML 2023
Investigating the Role of Model-Based Learning in Exploration and Transfer ICML 2023
Learning to Induce Causal Structure ICLR 2023
Procedural generalization by planning with self-supervised world models ICLR 2022
Retrieval-Augmented Reinforcement Learning ICML 2022
Large-Scale Retrieval for Reinforcement Learning NIPS 2022
On the role of planning in model-based deep reinforcement learning ICLR 2021
Counterfactual Credit Assignment in Model-Free Reinforcement Learning ICML 2021
Muesli: Combining Improvements in Policy Optimization ICML 2021
Value-driven Hindsight Modelling NIPS 2020
Combining Q-Learning and Search with Amortized Value Estimates ICLR 2020
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions AISTATS 2020
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search ICLR 2019
Credit Assignment Techniques in Stochastic Computation Graphs AISTATS 2019
Temporal Difference Variational Auto-Encoder ICLR 2019
An Investigation of Model-Free Planning ICML 2019
Single-Agent Policy Tree Search With Guarantees NIPS 2018
Relational recurrent neural networks NIPS 2018
Learning to search with MCTSnets ICML 2018
Imagination-Augmented Agents for Deep Reinforcement Learning NIPS 2017
Visual Interaction Networks: Learning a Physics Simulator from Video NIPS 2017
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models NIPS 2016
Gradient Estimation Using Stochastic Computation Graphs NIPS 2015