Zhongkai Hao

According to our database¹, Zhongkai Hao authored at least 23 papers between 2020 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2024

DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training.

[BibT_eX]

[DOI]

CoRR, 2024

Your Diffusion Model is Secretly a Certifiably Robust Classifier.

[BibT_eX]

[DOI]

CoRR, 2024

Preconditioning for Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Improved Operator Learning by Orthogonal Attention.

[BibT_eX]

[DOI]

CoRR, 2023

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.

[BibT_eX]

[DOI]

CoRR, 2023

Reward Informed Dreamer for Task Generalization in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Full-Atom Protein Pocket Design via Iterative Refinement.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Reuse Bias in Off-Policy Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

GNOT: A General Neural Operator Transformer for Operator Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Equivariant Energy-Guided SDE for Inverse Molecular Design.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Towards Exploring Large Molecular Space: An Efficient Chemical Genetic Algorithm.

[BibT_eX]

[DOI]

J. Comput. Sci. Technol., 2022

Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications.

[BibT_eX]

[DOI]

CoRR, 2022

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

AVT: Au-Assisted Visual Transformer for Facial Expression Recognition.

[BibT_eX]

[DOI]

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

A two-stage 3D CNN based learning method for spontaneous micro-expression recognition.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Query-based Adversarial Attacks on Graph with Fake Nodes.

[BibT_eX]

[DOI]

CoRR, 2021

2020

ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction.

[BibT_eX]

[DOI]

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Zhongkai Hao

Timeline

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On csauthors.net:

Bibliography

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