Zhongkai Hao

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 35

Top Topics

Iterative Refinement

Expression Recognition

Top Venues

Publications

Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu
Your Diffusion Model is Secretly a Certifiably Robust Classifier. CoRR (2024)
Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren, Dong Ni
PAPM: A Physics-aware Proxy Model for Process Systems. CoRR (2024)
Songming Liu, Chang Su, Jiachen Yao, Zhongkai Hao, Hang Su, Youjia Wu, Jun Zhu
Preconditioning for Physics-Informed Neural Networks. CoRR (2024)
Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. CoRR (2024)
Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. CoRR (2024)
Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. ICLR (2024)
Ze Cheng, Zhongkai Hao, Xiaoqiang Wang, Jianing Huang, Youjia Wu, Xudan Liu, Yiru Zhao, Songming Liu, Hang Su
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations. CoRR (2024)
Chengyang Ying, Zhongkai Hao, Xinning Zhou, Xuezhou Xu, Hang Su, Xingxing Zhang, Jun Zhu
PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning. CoRR (2024)
Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu
MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. CoRR (2023)
Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su
Improved Operator Learning by Orthogonal Attention. CoRR (2023)
Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu
NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. CoRR (2023)
Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu
NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. ICML (2023)
Zhongkai Hao, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. CoRR (2023)
Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu
MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. ICML (2023)
Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu
Full-Atom Protein Pocket Design via Iterative Refinement. NeurIPS (2023)
Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng
Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients. ICLR (2023)
Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
Equivariant Energy-Guided SDE for Inverse Molecular Design. ICLR (2023)
Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Songming Liu, Jialian Li, Dong Yan, Jun Zhu
Reward Informed Dreamer for Task Generalization in Reinforcement Learning. CoRR (2023)
Zhongkai Hao, Chengyang Ying, Zhengyi Wang, Hang Su, Yinpeng Dong, Songming Liu, Ze Cheng, Jun Zhu, Jian Song
GNOT: A General Neural Operator Transformer for Operator Learning. CoRR (2023)
Zhongkai Hao, Zhengyi Wang, Hang Su, Chengyang Ying, Yinpeng Dong, Songming Liu, Ze Cheng, Jian Song, Jun Zhu
GNOT: A General Neural Operator Transformer for Operator Learning. ICML (2023)
Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu
On the Reuse Bias in Off-Policy Reinforcement Learning. IJCAI (2023)
Zhongkai Hao, Songming Liu, Yichi Zhang, Chengyang Ying, Yao Feng, Hang Su, Jun Zhu
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications. CoRR (2022)
Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Ze Cheng
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. CoRR (2022)
Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu
Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors. IJCAI (2022)
Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu
On the Reuse Bias in Off-Policy Reinforcement Learning. CoRR (2022)
Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jian Song, Jun Zhu
GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing. ICML (2022)
Rijin Jin, Sirui Zhao, Zhongkai Hao, Yifan Xu, Tong Xu, Enhong Chen
AVT: Au-Assisted Visual Transformer for Facial Expression Recognition. ICIP (2022)
Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
Equivariant Energy-Guided SDE for Inverse Molecular Design. CoRR (2022)
Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng
Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients. CoRR (2022)
Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jun Zhu, Jian Song
GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing. CoRR (2022)
Jian-Fu Zhu, Zhongkai Hao, Qi Liu, Yu Yin, Chengqiang Lu, Zhenya Huang, En-Hong Chen
Towards Exploring Large Molecular Space: An Efficient Chemical Genetic Algorithm. J. Comput. Sci. Technol. 37 (6) (2022)
Zhengyi Wang, Zhongkai Hao, Hang Su, Jun Zhu
Query-based Adversarial Attacks on Graph with Fake Nodes. CoRR (2021)
Sirui Zhao, Hanqing Tao, Yangsong Zhang, Tong Xu, Kun Zhang, Zhongkai Hao, Enhong Chen
A two-stage 3D CNN based learning method for spontaneous micro-expression recognition. Neurocomputing 448 (2021)
Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. KDD (2020)
Zhongkai Hao, Chengqiang Lu, Zheyuan Hu, Hao Wang, Zhenya Huang, Qi Liu, Enhong Chen, Cheekong Lee
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. CoRR (2020)