11 citations · 26 across the 7 of their papers we have counts for
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cs.LG2023★ 3 cited
Residual Q-Learning: Offline and Online Policy Customization without Value
Chenran Li, Chen Tang, Haruki Nishimura +3
Imitation Learning (IL) is a widely used framework for learning imitative behavior from demonstrations. It is especially appealing for solving complex real-world tasks where handcr…
cs.RO2023★ 5 cited
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States
Fernando Castañeda, Haruki Nishimura, Rowan McAllister +2
Learning-based control approaches have shown great promise in performing complex tasks directly from high-dimensional perception data for real robotic systems. Nonetheless, the lea…