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Jiaqi Han
Jiaqi Han
Verified email at stanford.edu - Homepage
Title
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Cited by
Year
Multivariate time series anomaly detection and interpretation using hierarchical inter-metric and temporal embedding
Z Li, Y Zhao, J Han, Y Su, R Jiao, X Wen, D Pei
Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021
273*2021
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
J Han, J Cen, L Wu, Z Li, X Kong, R Jiao, Z Yu, T Xu, F Wu, Z Wang, H Xu, ...
arXiv preprint arXiv:2403.00485, 2024
90*2024
Equivariant Graph Mechanics Networks with Constraints
W Huang*, J Han*, Y Rong, T Xu, F Sun, J Huang
International Conference on Learning Representations (ICLR 2022), 2022
742022
Energy-motivated equivariant pretraining for 3d molecular graphs
R Jiao, J Han, W Huang, Y Rong, Y Liu
AAAI Conference on Artificial Intelligence (AAAI 2023), 2022
52*2022
Crystal structure prediction by joint equivariant diffusion
R Jiao, W Huang, P Lin, J Han, P Chen, Y Lu, Y Liu
Advances in Neural Information Processing Systems 36, 2024
46*2024
Learning Physical Dynamics with Subequivariant Graph Neural Networks
J Han, W Huang, H Ma, J Li, JB Tenenbaum, C Gan
Advances in Neural Information Processing Systems (NeurIPS 2022), 2022
392022
Smoothing matters: Momentum transformer for domain adaptive semantic segmentation
R Chen, Y Rong, S Guo, J Han, F Sun, T Xu, W Huang
arXiv preprint arXiv:2203.07988, 2022
242022
Equivariant Graph Hierarchy-Based Neural Networks
J Han, W Huang, T Xu, Y Rong
Advances in Neural Information Processing Systems (NeurIPS 2022), 2022
242022
Equivariant graph neural operator for modeling 3d dynamics
M Xu, J Han, A Lou, J Kossaifi, A Ramanathan, K Azizzadenesheli, ...
arXiv preprint arXiv:2401.11037, 2024
112024
RelBench: A benchmark for deep learning on relational databases
J Robinson, R Ranjan, W Hu, K Huang, J Han, A Dobles, M Fey, ...
arXiv preprint arXiv:2407.20060, 2024
42024
Subequivariant Graph Reinforcement Learning in 3D Environments
R Chen*, J Han*, F Sun, W Huang
International Conference on Machine Learning (ICML 2023), 2023
42023
Tfg: Unified training-free guidance for diffusion models
H Ye, H Lin, J Han, M Xu, S Liu, Y Liang, J Ma, J Zou, S Ermon
arXiv preprint arXiv:2409.15761, 2024
32024
Structure-Aware DropEdge Toward Deep Graph Convolutional Networks
J Han, W Huang, Y Rong, T Xu, F Sun, J Huang
IEEE Transactions on Neural Networks and Learning Systems, 2023
22023
Geometric Trajectory Diffusion Models
J Han, M Xu, A Lou, H Ye, S Ermon
arXiv preprint arXiv:2410.13027, 2024
12024
Img2cad: Reverse engineering 3d cad models from images through vlm-assisted conditional factorization
Y You, MA Uy, J Han, R Thomas, H Zhang, S You, L Guibas
arXiv preprint arXiv:2408.01437, 2024
12024
-PO: Generalizing Preference Optimization with -divergence Minimization
J Han, M Jiang, Y Song, J Leskovec, S Ermon, M Xu
arXiv preprint arXiv:2410.21662, 2024
2024
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
J Kazdan, H Sun, J Han, F Petersen, S Ermon
arXiv preprint arXiv:2409.07025, 2024
2024
Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design
S Nagaraj, J Han, A Garg, M Xu
ICML'24 Workshop ML for Life and Material Science: From Theory to Industry …, 2024
2024
Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning
Y Zhang, J Cen, J Han, Z Zhang, J Zhou, W Huang
Forty-first International Conference on Machine Learning, 2024
2024
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Articles 1–19