Matteo Hessel

21 papers · 2016–2022 · 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 ↓

+11 more ↓

🗺️ Taxonomy Completionist (28) 🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🔬 Deep Specialist (15) 👑 Triple Crown 🤝 Dynamic Duo (15) 🏆 Grand Slam ⚡ Prolific Year · Productive 🔥 Unstoppable · Bronze ❓ The Questioner (2) 💎 Century Club · Bronze 🚀 Conference Pioneer 📈 Trend Setter 🗃️ Keyword Collector (87)

Venues

NeurIPS (8) ICML (7) ICLR (4) AAAI (2)

Top co-authors

David Silver (15) Hado van Hasselt (8) Hado P van Hasselt (8) Zhongwen Xu (7) Junhyuk Oh (6) Satinder P. Singh (4) Andre Barreto (3) Satinder Singh (3) Vivek Veeriah (3) Tom Schaul (3)

Research topics

Reinforcement Learning (19) Methods (18) Artificial Intelligence (12) Machine Learning (12) Core AI (9) Applications (7) Learning Types · Machine Learning (7) Learning Paradigms · Artificial Intelligence (6) Deep Learning (4) Optimization & Theory · Machine Learning (4) Learning Paradigms · Machine Learning (3) Learning Types · Deep Learning (2) Architectures (1) Core Methods (1) Optimization & Theory · Deep Learning (1)

Keywords

reinforcement learning (9) deep reinforcement learning (6) policy gradient (3) value function (3) off-policy learning (3) atari game (3) temporal difference learning (3) model-based reinforcement learning (3) auxiliary task (2) experience replay (2) value function estimation (2) function approximation (2) successor feature (2) reward function (2) value iteration (2) credit assignment (2) online learning (2) policy learning (1) distributed learning (1) reproducible research (1)

Papers

Learning by Directional Gradient Descent ICLR 2022 Discovery of Options via Meta-Learned Subgoals NeurIPS 2021 Emphatic Algorithms for Deep Reinforcement Learning ICML 2021 Expected Eligibility Traces AAAI 2021 Muesli: Combining Improvements in Policy Optimization ICML 2021 Self-Consistent Models and Values NeurIPS 2021 A Self-Tuning Actor-Critic Algorithm NeurIPS 2020 Behaviour Suite for Reinforcement Learning ICLR 2020 Discovering Reinforcement Learning Algorithms NeurIPS 2020 Meta-Gradient Reinforcement Learning with an Objective Discovered Online NeurIPS 2020 Off-Policy Actor-Critic with Shared Experience Replay ICML 2020 What Can Learned Intrinsic Rewards Capture? ICML 2020 Discovery of Useful Questions as Auxiliary Tasks NeurIPS 2019 Multi-Task Deep Reinforcement Learning with PopArt AAAI 2019 When to use parametric models in reinforcement learning? NeurIPS 2019 Distributed Prioritized Experience Replay ICLR 2018 Noisy Networks For Exploration ICLR 2018 Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement ICML 2018 The Predictron: End-To-End Learning and Planning ICML 2017 Dueling Network Architectures for Deep Reinforcement Learning ICML 2016 Learning values across many orders of magnitude NeurIPS 2016