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20232026
most citedMission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications

2 citations · 3 across the 5 of their papers we have counts for

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cs.LG2026

PHDME: Physics-Informed Diffusion Models without Explicit Governing Equations

Kaiyuan Tan, Kendra Givens, Peilun Li +1

Diffusion models provide expressive priors for forecasting trajectories of dynamical systems, but are typically unreliable in the sparse data regime. Physics-informed machine learn…

cs.LG2024★ 1 cited

Physics-Constrained Learning for PDE Systems with Uncertainty Quantified Port-Hamiltonian Models

Kaiyuan Tan, Peilun Li, Thomas Beckers

Modeling the dynamics of flexible objects has become an emerging topic in the community as these objects become more present in many applications, e.g., soft robotics. Due to the p…