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06/09/2023
Self-Paced Absolute Learning Progress as a Regularized Approach to Curriculum Learning
The usability of Reinforcement Learning is restricted by the large compu...
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11/02/2022
Variational Hierarchical Mixtures for Learning Probabilistic Inverse Dynamics
Well-calibrated probabilistic regression models are a crucial learning c...
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04/22/2021
Reinforcement Learning using Guided Observability
Due to recent breakthroughs, reinforcement learning (RL) has demonstrate...
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02/25/2021
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning
Across machine learning, the use of curricula has shown strong empirical...
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11/10/2020
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning
Probabilistic regression techniques in control and robotics applications...
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04/24/2020
Self-Paced Deep Reinforcement Learning
Generalization and reuse of agent behaviour across a variety of learning...
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11/01/2019
Generalized Mean Estimation in Monte-Carlo Tree Search
We consider Monte-Carlo Tree Search (MCTS) applied to Markov Decision Pr...
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10/07/2019