Theophane Weber

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

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

Jump to papers ↓

+10 more ↓

🗺️ Taxonomy Completionist (40) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

👑 Triple Crown 🔬 Deep Specialist (10) 🧬 Topic Evolution 🏆 Keyword Champion (2) 🧭 Keyword Pioneer 🤝 Dynamic Duo (10) 🗃️ Keyword Collector (106) 📈 Trend Setter 🔥 Unstoppable · Bronze 💎 Century Club · Bronze

Venues

NeurIPS (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)

Research topics

Reinforcement Learning (15) Artificial Intelligence (14) Machine Learning (13) Core AI · Artificial Intelligence (11) Methods (11) Learning Types · Machine Learning (9) Deep Learning (8) Applications (6) Core Methods (4) Learning Types · Deep Learning (4) Optimization & Theory (4) Bayesian & Probabilistic (3) Computer Vision (2) Architectures (2) Core AI · Computer Vision (2)

Keywords

reinforcement learning (6) model-based reinforcement learning (5) value function (5) monte carlo tree search (4) neural network (4) variance reduction (4) credit assignment (3) policy gradient (3) model-free reinforcement learning (3) deep reinforcement learning (3) model learning (2) offline reinforcement learning (2) retrieval-augmented generation (2) probabilistic inference (2) model-based rl (2) counterfactual reasoning (2) world model (2) tree search (2) variational autoencoder (2) planning algorithm (2)

Papers

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