12 citations · 29 across the 5 of their papers we have counts for
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cs.RO2024
Efficient Imitation Without Demonstrations via Value-Penalized Auxiliary Control from Examples
Trevor Ablett, Bryan Chan, Jayce Haoran Wang +1
Common approaches to providing feedback in reinforcement learning are the use of hand-crafted rewards or full-trajectory expert demonstrations. Alternatively, one can use examples…
cs.RO2020★ 8 cited
Heteroscedastic Uncertainty for Robust Generative Latent Dynamics
Oliver Limoyo, Bryan Chan, Filip Marić +3
Learning or identifying dynamics from a sequence of high-dimensional observations is a difficult challenge in many domains, including reinforcement learning and control. The proble…