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Pierre-Luc Bacon

23 papers · 2018–2025 · 5 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

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+9 more ↓ πŸ—ΊοΈ Taxonomy Completionist (35) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🧬 Topic Evolution πŸ”¬ Deep Specialist (10) πŸ† Grand Slam πŸ‘‘ Triple Crown ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze ❓ The Questioner (2) πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (125)

Venues

ICLR (7) ICML (7) NeurIPS (6) AAAI (2) AISTATS (1)

Top co-authors

Clement Gehring (3) Evgenii Nikishin (3) Pierluca D'Oro (3) Martin Klissarov (3) Pascal Vincent (3) Doina Precup (3) Michel Ma (3) Tianwei Ni (3) David Kanaa (2) Max Schwarzer (2)

Research topics

Machine Learning (19) Reinforcement Learning (15) Learning Types Β· Machine Learning (15) Methods (15) Artificial Intelligence (12) Core AI (12) Deep Learning (9) Applications (5) Learning Types Β· Deep Learning (5) Optimization & Theory (5) Architectures (4) Core Methods (4) Natural Language Processing (2) Application Areas (2) Models (2)

Keywords

reinforcement learning (8) policy gradient (3) sample efficiency (3) deep reinforcement learning (2) reward function (2) policy optimization (2) continuous control (2) large language model (2) stochastic gradient descent (1) imitation learning (1) representation learning (1) few-shot learning (1) maximum entropy (1) robustness (1) off-policy evaluation (1) contrastive learning (1) attention mechanism (1) self-supervised learning (1) constrained reinforcement learning (1) function approximation (1)

Papers

MaestroMotif: Skill Design from Artificial Intelligence Feedback ICLR 2025 Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning ICML 2025 Scaling Trends in Language Model Robustness ICML 2025 Bridging State and History Representations: Understanding Self-Predictive RL ICLR 2024 Course Correcting Koopman Representations ICLR 2024 Decoupling regularization from the action space ICLR 2024 Do Transformer World Models Give Better Policy Gradients? ICML 2024 Maximum entropy GFlowNets with soft Q-learning AISTATS 2024 Motif: Intrinsic Motivation from Artificial Intelligence Feedback ICLR 2024 Block-State Transformers NeurIPS 2023 Double Gumbel Q-Learning NeurIPS 2023 Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control NeurIPS 2023 Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier ICLR 2023 When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment NeurIPS 2023 Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation AAAI 2022 Direct Behavior Specification via Constrained Reinforcement Learning ICML 2022 Myriad: a real-world testbed to bridge trajectory optimization and deep learning NeurIPS 2022 The Primacy Bias in Deep Reinforcement Learning ICML 2022 Neural Algorithmic Reasoners are Implicit Planners NeurIPS 2021 Options of Interest: Temporal Abstraction with Interest Functions AAAI 2020 Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling ICML 2020 Convergent Tree Backup and Retrace with Function Approximation ICML 2018