ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. - Zhongkai Hao; Chengqiang Lu; Zhenya Huang; Hao Wang 076; Zheyuan Hu 002; Qi Liu 003; Enhong Chen; Cheekong Lee (KDD, 2020)

Query-based Adversarial Attacks on Graph with Fake Nodes. - Zhengyi Wang; Zhongkai Hao; Hang Su 006; Jun Zhu 001 (CoRR, 2021)

A two-stage 3D CNN based learning method for spontaneous micro-expression recognition. - Sirui Zhao; Hanqing Tao; Yangsong Zhang; Tong Xu 001; Kun Zhang 015; Zhongkai Hao; Enhong Chen (Neurocomputing, 2021)

AVT: Au-Assisted Visual Transformer for Facial Expression Recognition. - Rijin Jin; Sirui Zhao; Zhongkai Hao; Yifan Xu; Tong Xu 001; Enhong Chen (ICIP, 2022)

GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing. - Zhongkai Hao; Chengyang Ying; Yinpeng Dong; Hang Su 006; Jian Song; Jun Zhu 001 (ICML, 2022)

Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors. - Zhengyi Wang; Zhongkai Hao; Ziqiao Wang; Hang Su 006; Jun Zhu 001 (IJCAI, 2022)

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. - Songming Liu; Zhongkai Hao; Chengyang Ying; Hang Su 006; Jun Zhu 001; Ze Cheng (NeurIPS, 2022)

Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications. - Zhongkai Hao; Songming Liu; Yichi Zhang; Chengyang Ying; Yao Feng 002; Hang Su 006; Jun Zhu 001 (CoRR, 2022)

Towards Exploring Large Molecular Space: An Efficient Chemical Genetic Algorithm. - Jian-Fu Zhu; Zhongkai Hao; Qi Liu 003; Yu Yin 002; Chengqiang Lu; Zhenya Huang; En-Hong Chen (J. Comput. Sci. Technol., 2022)

Equivariant Energy-Guided SDE for Inverse Molecular Design. - Fan Bao; Min Zhao 013; Zhongkai Hao; Peiyao Li; Chongxuan Li; Jun Zhu 001 (ICLR, 2023)

Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients. - Zhongkai Hao; Chengyang Ying; Hang Su 006; Jun Zhu 001; Jian Song; Ze Cheng (ICLR, 2023)

GNOT: A General Neural Operator Transformer for Operator Learning. - Zhongkai Hao; Zhengyi Wang; Hang Su 006; Chengyang Ying; Yinpeng Dong; Songming Liu; Ze Cheng; Jian Song; Jun Zhu 001 (ICML, 2023)

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. - Songming Liu; Zhongkai Hao; Chengyang Ying; Hang Su 006; Ze Cheng; Jun Zhu 001 (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 006; Jun Zhu 001 (ICML, 2023)

On the Reuse Bias in Off-Policy Reinforcement Learning. - Chengyang Ying; Zhongkai Hao; Xinning Zhou; Hang Su 006; Dong Yan; Jun Zhu 001 (IJCAI, 2023)

Full-Atom Protein Pocket Design via Iterative Refinement. - Zaixi Zhang; Zepu Lu; Zhongkai Hao; Marinka Zitnik; Qi Liu 003 (NeurIPS, 2023)

Reward Informed Dreamer for Task Generalization in Reinforcement Learning. - Chengyang Ying; Zhongkai Hao; Xinning Zhou; Hang Su 006; Songming Liu; Jialian Li; Dong Yan; Jun Zhu 001 (CoRR, 2023)

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. - Hong Wang 028; Zhongkai Hao; Jie Wang 005; Zijie Geng; Zhen Wang; Bin Li 025; Feng Wu 001 (ICLR, 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 006 (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 006; Anima Anandkumar; Jian Song; Jun Zhu 001 (ICML, 2024)

PAPM: A Physics-aware Proxy Model for Process Systems. - Pengwei Liu; Zhongkai Hao; Xingyu Ren; Hangjie Yuan; Jiayang Ren; Dong Ni 002 (ICML, 2024)

Improved Operator Learning by Orthogonal Attention. - Zipeng Xiao; Zhongkai Hao; Bokai Lin; Zhijie Deng; Hang Su 006 (ICML, 2024)

Diffusion Models are Certifiably Robust Classifiers. - Huanran Chen; Yinpeng Dong; Shitong Shao; Zhongkai Hao; Xiao Yang; Hang Su 006; Jun Zhu 001 (NeurIPS, 2024)

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. - Zhongkai Hao; Jiachen Yao; Chang Su; Hang Su 006; Ziao Wang; Fanzhi Lu; Zeyu Xia 003; Yichi Zhang; Songming Liu; Lu Lu; Jun Zhu 001 (NeurIPS, 2024)

Amortized Fourier Neural Operators. - Zipeng Xiao; Siqi Kou; Zhongkai Hao; Bokai Lin; Zhijie Deng (NeurIPS, 2024)

PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning. - Chengyang Ying; Zhongkai Hao; Xinning Zhou; Xuezhou Xu; Hang Su 006; Xingxing Zhang 001; Jun Zhu 001 (NeurIPS, 2024)

Preconditioning for Physics-Informed Neural Networks. - Songming Liu; Chang Su; Jiachen Yao; Zhongkai Hao; Hang Su 006; Youjia Wu; Jun Zhu 001 (CoRR, 2024)

Your Diffusion Model is Secretly a Certifiably Robust Classifier. - Huanran Chen; Yinpeng Dong; Shitong Shao; Zhongkai Hao; Xiao Yang; Hang Su 006; Jun Zhu 001 (CoRR, 2024)

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 002 (AAAI, 2025)

Exploratory Diffusion Policy for Unsupervised Reinforcement Learning. - Chengyang Ying; Huayu Chen; Xinning Zhou; Zhongkai Hao; Hang Su 006; Jun Zhu 001 (CoRR, 2025)

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators. - Ze Cheng; Zhuoyu Li; Xiaoqiang Wang; Jianing Huang; Zhizhou Zhang; Zhongkai Hao; Hang Su 006 (CoRR, 2025)

AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation. - Hengkai Tan; Yao Feng 002; Xinyi Mao; Shuhe Huang; Guodong Liu; Zhongkai Hao; Hang Su 006; Jun Zhu 001 (CoRR, 2025)