Zhongkai Hao - RankMe

53 papers A* 22B 1Journal 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Helix: Evolutionary Reinforcement Learning for Open-Ended Scientific Problem Solving. CoRR Chang Su, Zhongkai Hao, Zhizhou Zhang, Zeyu Xia, Youjia Wu, Hang Su, Jun Zhu
2026	J	`jnl`	Pretrain Finite Element Method: A Pretraining and Warm-start Framework for PDEs via Physics-Informed Neural Operators. CoRR Yizheng Wang, Zhongkai Hao, Mohammad Sadegh Eshaghi, Cosmin Anitescu, Xiaoying Zhuang, Timon Rabczuk, Yinghua Liu
2025	J	`jnl`	A CoRR Fengji Zhang, Xinyao Niu, Chengyang Ying, Guancheng Lin, Zhongkai Hao, Zhou Fan, Chengen Huang, Jacky Keung, Bei Chen, Junyang Lin
2025	A*	`conf`	Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators. ICML Ze Cheng, Zhuoyu Li, Xiaoqiang Wang, Jianing Huang, Zhizhou Zhang, Zhongkai Hao, Hang Su
2025	J	`jnl`	Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators. CoRR Ze Cheng, Zhuoyu Li, Xiaoqiang Wang, Jianing Huang, Zhizhou Zhang, Zhongkai Hao, Hang Su
2025	A*	`conf`	AeroGTO: An Efficient Graph-Transformer Operator for Learning Large-Scale Aerodynamics of 3D Vehicle Geometries. AAAI Pengwei Liu, Pengkai Wang, Xingyu Ren, Hangjie Yuan, Zhongkai Hao, Chao Xu, Shengze Cai, Dong Ni
2025	J	`jnl`	An Efficient Graph-Transformer Operator for Learning Physical Dynamics with Manifolds Embedding. CoRR Pengwei Liu, Xingyu Ren, Pengkai Wang, Hangjie Yuan, Zhongkai Hao, Guanyu Chen, Chao Xu, Dong Ni, Shengze Cai
2025	J	`jnl`	AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation. CoRR Hengkai Tan, Yao Feng, Xinyi Mao, Shuhe Huang, Guodong Liu, Zhongkai Hao, Hang Su, Jun Zhu
2025	J	`jnl`	Exploratory Diffusion Policy for Unsupervised Reinforcement Learning. CoRR Chengyang Ying, Huayu Chen, Xinning Zhou, Zhongkai Hao, Hang Su, Jun Zhu
2024	A*	`conf`	Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. ICLR Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
2024	J	`jnl`	Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. CoRR Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
2024	A*	`conf`	Amortized Fourier Neural Operators. NeurIPS Zipeng Xiao, Siqi Kou, Zhongkai Hao, Bokai Lin, Zhijie Deng
2024	A*	`conf`	DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. ICML Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu
2024	J	`jnl`	DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. CoRR Zhongkai Hao, Chang Su, Songming Liu, Julius Berner, Chengyang Ying, Hang Su, Anima Anandkumar, Jian Song, Jun Zhu
2024	A*	`conf`	Diffusion Models are Certifiably Robust Classifiers. NeurIPS Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu
2024	A*	`conf`	Improved Operator Learning by Orthogonal Attention. ICML Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su
2024	A*	`conf`	PAPM: A Physics-aware Proxy Model for Process Systems. ICML Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren, Dong Ni
2024	J	`jnl`	PAPM: A Physics-aware Proxy Model for Process Systems. CoRR Pengwei Liu, Zhongkai Hao, Xingyu Ren, Hangjie Yuan, Jiayang Ren, Dong Ni
2024	A*	`conf`	PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning. NeurIPS Chengyang Ying, Zhongkai Hao, Xinning Zhou, Xuezhou Xu, Hang Su, Xingxing Zhang, Jun Zhu
2024	J	`jnl`	PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning. CoRR Chengyang Ying, Zhongkai Hao, Xinning Zhou, Xuezhou Xu, Hang Su, Xingxing Zhang, Jun Zhu
2024	A*	`conf`	PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. NeurIPS Zhongkai Hao, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu
2024	J	`jnl`	Preconditioning for Physics-Informed Neural Networks. CoRR Songming Liu, Chang Su, Jiachen Yao, Zhongkai Hao, Hang Su, Youjia Wu, Jun Zhu
2024	A*	`conf`	Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations. ICML Ze Cheng, Zhongkai Hao, Xiaoqiang Wang, Jianing Huang, Youjia Wu, Xudan Liu, Yiru Zhao, Songming Liu, Hang Su
2024	J	`jnl`	Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations. CoRR Ze Cheng, Zhongkai Hao, Xiaoqiang Wang, Jianing Huang, Youjia Wu, Xudan Liu, Yiru Zhao, Songming Liu, Hang Su
2024	J	`jnl`	Your Diffusion Model is Secretly a Certifiably Robust Classifier. CoRR Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu
2023	A*	`conf`	Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients. ICLR Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng
2023	A*	`conf`	Equivariant Energy-Guided SDE for Inverse Molecular Design. ICLR Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
2023	A*	`conf`	Full-Atom Protein Pocket Design via Iterative Refinement. NeurIPS Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu
2023	A*	`conf`	GNOT: A General Neural Operator Transformer for Operator Learning. ICML Zhongkai Hao, Zhengyi Wang, Hang Su, Chengyang Ying, Yinpeng Dong, Songming Liu, Ze Cheng, Jian Song, Jun Zhu
2023	J	`jnl`	GNOT: A General Neural Operator Transformer for Operator Learning. CoRR Zhongkai Hao, Chengyang Ying, Zhengyi Wang, Hang Su, Yinpeng Dong, Songming Liu, Ze Cheng, Jun Zhu, Jian Song
2023	J	`jnl`	Improved Operator Learning by Orthogonal Attention. CoRR Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su
2023	A*	`conf`	MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. ICML Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu
2023	J	`jnl`	MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. CoRR Jiachen Yao, Chang Su, Zhongkai Hao, Songming Liu, Hang Su, Jun Zhu
2023	A*	`conf`	NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. ICML Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu
2023	J	`jnl`	NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. CoRR Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Ze Cheng, Jun Zhu
2023	A*	`conf`	On the Reuse Bias in Off-Policy Reinforcement Learning. IJCAI Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu
2023	J	`jnl`	PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. CoRR Zhongkai Hao, Jiachen Yao, Chang Su, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, Jun Zhu
2023	J	`jnl`	Reward Informed Dreamer for Task Generalization in Reinforcement Learning. CoRR Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Songming Liu, Jialian Li, Dong Yan, Jun Zhu
2022	A*	`conf`	A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. NeurIPS Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Ze Cheng
2022	J	`jnl`	A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. CoRR Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Ze Cheng
2022	B	`conf`	AVT: Au-Assisted Visual Transformer for Facial Expression Recognition. ICIP Rijin Jin, Sirui Zhao, Zhongkai Hao, Yifan Xu, Tong Xu, Enhong Chen
2022	J	`jnl`	Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients. CoRR Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Jian Song, Ze Cheng
2022	A*	`conf`	Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors. IJCAI Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu
2022	J	`jnl`	Equivariant Energy-Guided SDE for Inverse Molecular Design. CoRR Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
2022	A*	`conf`	GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing. ICML Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jian Song, Jun Zhu
2022	J	`jnl`	GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing. CoRR Zhongkai Hao, Chengyang Ying, Yinpeng Dong, Hang Su, Jun Zhu, Jian Song
2022	J	`jnl`	On the Reuse Bias in Off-Policy Reinforcement Learning. CoRR Chengyang Ying, Zhongkai Hao, Xinning Zhou, Hang Su, Dong Yan, Jun Zhu
2022	J	`jnl`	Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications. CoRR Zhongkai Hao, Songming Liu, Yichi Zhang, Chengyang Ying, Yao Feng, Hang Su, Jun Zhu
2022	J	`jnl`	Towards Exploring Large Molecular Space: An Efficient Chemical Genetic Algorithm. J. Comput. Sci. Technol. Jian-Fu Zhu, Zhongkai Hao, Qi Liu, Yu Yin, Chengqiang Lu, Zhenya Huang, En-Hong Chen
2021	J	`jnl`	A two-stage 3D CNN based learning method for spontaneous micro-expression recognition. Neurocomputing Sirui Zhao, Hanqing Tao, Yangsong Zhang, Tong Xu, Kun Zhang, Zhongkai Hao, Enhong Chen
2021	J	`jnl`	Query-based Adversarial Attacks on Graph with Fake Nodes. CoRR Zhengyi Wang, Zhongkai Hao, Hang Su, Jun Zhu
2020	A*	`conf`	ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. KDD Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee
2020	J	`jnl`	ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. CoRR Zhongkai Hao, Chengqiang Lu, Zheyuan Hu, Hao Wang, Zhenya Huang, Qi Liu, Enhong Chen, Cheekong Lee