8 papers
How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
Xiaoyuan Cheng, Wenxuan Yuan, Boyang Li +7
Diffusion policy sampling enables reinforcement learning (RL) to represent multimodal action distributions beyond suboptimal unimodal Gaussian policies. However, existing diffusion…
From Embedding to Control: Representations for Stochastic Multi-Object Systems
Xiaoyuan Cheng, Yiming Yang, Wei Jiang +3
This paper studies how to achieve accurate modeling and effective control in stochastic nonlinear dynamics with multiple interacting objects. However, non-uniform interactions and…
Fast-Forward Lattice Boltzmann: Learning Kinetic Behaviour with Physics-Informed Neural Operators
Xiao Xue, Marco F. P. ten Eikelder, Mingyang Gao +7
The lattice Boltzmann equation (LBE), rooted in kinetic theory, provides a powerful framework for capturing complex flow behaviour by describing the evolution of single-particle di…
Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction
Yi He, Yiming Yang, Xiaoyuan Cheng +4
Generating long-term trajectories of dissipative chaotic systems autoregressively is a highly challenging task. The inherent positive Lyapunov exponents amplify prediction errors o…
Learning Chaos In A Linear Way
Xiaoyuan Cheng, Yi He, Yiming Yang +5
Learning long-term behaviors in chaotic dynamical systems, such as turbulent flows and climate modelling, is challenging due to their inherent instability and unpredictability. The…
Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
Yiming Yang, Xiaoyuan Cheng, Daniel Giles +5
Variational data assimilation estimates the dynamical system states by minimizing a cost function that fits the numerical models with the observational data. Although four-dimensio…
KEEC: Koopman Embedded Equivariant Control
Xiaoyuan Cheng, Yiming Yang, Xiaohang Tang +2
An efficient way to control systems with unknown nonlinear dynamics is to find an appropriate embedding or representation for simplified approximation (e.g. linearization), which f…
Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space
Xiaoyuan Cheng, Boli Chen, Liz Varga +1
This paper delves into the problem of safe reinforcement learning (RL) in a partially observable environment with the aim of achieving safe-reachability objectives. In traditional…