Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? - Chuwei Wang; Shanda Li; Di He 001; Liwei Wang 001 (NeurIPS, 2022)

Is L2 Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network? - Chuwei Wang; Shanda Li; Di He 001; Liwei Wang 001 (CoRR, 2022)

Model Predictive Control for Signal Temporal Logic Specifications with Time Interval Decomposition. - Xinyi Yu; Chuwei Wang; Dingran Yuan; Shaoyuan Li; Xiang Yin 003 (CDC, 2023)

Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo. - Ruichen Li; Haotian Ye; Du Jiang; Xuelan Wen; Chuwei Wang; Zhe Li; Xiang Li; Di He 001; Ji Chen; Weiluo Ren; Liwei Wang 001 (CoRR, 2023)

Self-Triggered Model Predictive Control for Signal Temporal Logic Tasks. - Junyue Huang; Chuwei Wang; Xinyi Yu; Xiang Yin 003 (CASE, 2024)

DOF: Accelerating High-order Differential Operators with Forward Propagation. - Ruichen Li; Chuwei Wang; Haotian Ye; Di He 001; Liwei Wang 001 (CoRR, 2024)

Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators. - Chuwei Wang; Julius Berner; Zongyi Li; Di Zhou; Jiayun Wang; Jane Bae; Anima Anandkumar (CoRR, 2024)

Sleep When Everything Looks Fine: Self-Triggered Monitoring for Signal Temporal Logic Tasks. - Chuwei Wang; Xinyi Yu; Jianing Zhao; Lars Lindemann; Xiang Yin 003 (IEEE Robotics Autom. Lett., 2024)

EquiReg: Equivariance Regularized Diffusion for Inverse Problems. - Bahareh Tolooshams; Aditi Chandrashekar; Rayhan Zirvi; Abbas Mammadov; Jiachen Yao; Chuwei Wang; Anima Anandkumar (CoRR, 2025)