Leonard Hasenclever
14 papers · 2017–2024 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (26) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π€
Dynamic Duo
(12)
π₯
Mega-Team Β· Squad
π§
Keyword Pioneer
π§¬
Topic Evolution
π
Trend Setter
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(69)
Top co-authors
Research topics
Machine Learning
(10)
Artificial Intelligence
(9)
Reinforcement Learning
(7)
Core AI
(6)
Learning Paradigms
(5)
Methods
(5)
Optimization & Theory
(5)
Applications
(4)
Learning Types
(4)
Deep Learning
(2)
Robotics
(2)
Capabilities
(2)
Mathematics & Optimization
(1)
Bayesian & Probabilistic
(1)
Core Methods
(1)
Keywords
reinforcement learning
(3)
model predictive control
(2)
continuous control
(2)
imitation learning
(2)
transfer learning
(2)
data efficiency
(2)
distributed learning
(1)
information bottleneck
(1)
probabilistic modeling
(1)
bayesian learning
(1)
multi-task learning
(1)
curriculum learning
(1)
variational inference
(1)
egocentric vision
(1)
active perception
(1)
policy learning
(1)
policy optimization
(1)
distributional reinforcement learning
(1)
human-robot interaction
(1)
stochastic gradient descent
(1)
Papers
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning
CoRL 2024
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
RSS 2024
Replay across Experiments: A Natural Extension of Off-Policy RL
ICLR 2024
Language to Rewards for Robotic Skill Synthesis
CoRL 2023
Behavior Priors for Efficient Reinforcement Learning
JMLR 2022
Evaluating Model-Based Planning and Planner Amortization for Continuous Control
ICLR 2022
Learning transferable motor skills with hierarchical latent mixture policies
ICLR 2022
A distributional view on multi-objective policy optimization
ICML 2020
CoMic: Complementary Task Learning & Mimicry for Reusable Skills
ICML 2020
Information asymmetry in KL-regularized RL
ICLR 2019
Neural Probabilistic Motor Primitives for Humanoid Control
ICLR 2019
Mix & Match Agent Curricula for Reinforcement Learning
ICML 2018
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server
JMLR 2017
Relativistic Monte Carlo
AISTATS 2017