Pierre-Luc Bacon
23 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (5) π Academic Marathon (7) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (12)
π
Cross-Pollinator
(12)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(27)
π
Triple Crown
π
Grand Slam
π§¬
Topic Evolution
β
The Questioner
(2)
π
Century Club
(23)
ποΈ
Keyword Collector
(81)
β‘
Prolific Year
(5)
π₯
Unstoppable
(6)
Conferences
ICLR (7)
ICML (7)
NIPS (6)
AAAI (2)
AISTATS (1)
Top co-authors
Keywords
reinforcement learning
(5)
continuous control
(2)
policy optimization
(2)
policy gradient
(2)
sample efficiency
(1)
off-policy evaluation
(1)
sequence modeling
(1)
importance sampling
(1)
maximum entropy
(1)
markov decision process
(1)
function approximation
(1)
attention mechanism
(1)
constrained reinforcement learning
(1)
language modeling
(1)
hierarchical reinforcement learning
(1)
markov chain monte carlo
(1)
imitation learning
(1)
maximum likelihood
(1)
contrastive learning
(1)
transformer architecture
(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
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
ICLR 2024
Maximum entropy GFlowNets with soft Q-learning
AISTATS 2024
Course Correcting Koopman Representations
ICLR 2024
Decoupling regularization from the action space
ICLR 2024
Bridging State and History Representations: Understanding Self-Predictive RL
ICLR 2024
Do Transformer World Models Give Better Policy Gradients?
ICML 2024
Double Gumbel Q-Learning
NIPS 2023
Block-State Transformers
NIPS 2023
Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
NIPS 2023
Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
ICLR 2023
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
NIPS 2023
Continuous-Time Meta-Learning with Forward Mode Differentiation
ICLR 2022
Direct Behavior Specification via Constrained Reinforcement Learning
ICML 2022
Myriad: a real-world testbed to bridge trajectory optimization and deep learning
NIPS 2022
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
AAAI 2022
The Primacy Bias in Deep Reinforcement Learning
ICML 2022
Neural Algorithmic Reasoners are Implicit Planners
NIPS 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