Hao, Zhongkai

19 publications

ICML 2025 Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators Ze Cheng, Zhuoyu Li, Wang Xiaoqiang, Jianing Huang, Zhizhou Zhang, Zhongkai Hao, Hang Su

AAAI 2025 AeroGTO: An Efficient Graph-Transformer Operator for Learning Large-Scale Aerodynamics of 3D Vehicle Geometries Pengwei Liu, Pengkai Wang, Xingyu Ren, Hangjie Yuan, Zhongkai Hao, Chao Xu, Shengze Cai, Dong Ni

ICLR 2024 Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu

NeurIPS 2024 Amortized Fourier Neural Operators Zipeng Xiao, Siqi Kou, Zhongkai Hao, Bokai Lin, Zhijie Deng

ICML 2024 DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu

NeurIPS 2024 Diffusion Models Are Certifiably Robust Classifiers Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu

ICML 2024 Improved Operator Learning by Orthogonal Attention Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su

ICML 2024 PAPM: A Physics-Aware Proxy Model for Process Systems Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren, Dong Ni

NeurIPS 2024 PEAC: Unsupervised Pre-Training for Cross-Embodiment Reinforcement Learning Chengyang Ying, Zhongkai Hao, Xinning Zhou, Xuezhou Xu, Hang Su, Xingxing Zhang, Jun Zhu

NeurIPS 2024 PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu

ICML 2024 Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations Ze Cheng, Zhongkai Hao, Xiaoqiang Wang, Jianing Huang, Youjia Wu, Xudan Liu, Yiru Zhao, Songming Liu, Hang Su

ICLR 2023 Bi-Level Physics-Informed Neural Networks for PDE Constrained Optimization Using Broyden's Hypergradients Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng

ICLR 2023 Equivariant Energy-Guided SDE for Inverse Molecular Design Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu

ICML 2023 GNOT: A General Neural Operator Transformer for Operator Learning Zhongkai Hao, Zhengyi Wang, Hang Su, Chengyang Ying, Yinpeng Dong, Songming Liu, Ze Cheng, Jian Song, Jun Zhu

ICML 2023 MultiAdam: Parameter-Wise Scale-Invariant Optimizer for Multiscale Training of Physics-Informed Neural Networks Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu

ICML 2023 NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu

IJCAI 2023 On the Reuse Bias in Off-Policy Reinforcement Learning Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu

IJCAI 2022 Cluster Attack: Query-Based Adversarial Attacks on Graph with Graph-Dependent Priors Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu

ICML 2022 GSmooth: Certified Robustness Against Semantic Transformations via Generalized Randomized Smoothing Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jian Song, Jun Zhu