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Yongqiang Chen
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Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
Y Chen, Y Zhang, Y Bian, H Yang, K Ma, B Xie, T Liu, B Han, J Cheng
Advances in Neural Information Processing Systems (NeurIPS 2022), 2022
99*2022
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
Y Chen, H Yang, Y Zhang, K Ma, T Liu, B Han, J Cheng
International Conference on Learning Representations (ICLR 2022), 2022
652022
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
Y Chen, K Zhou, Y Bian, B Xie, B Wu, Y Zhang, K Ma, H Yang, P Zhao, ...
International Conference on Learning Representations (ICLR 2023); Oral …, 2022
362022
Self-enhanced gnn: Improving graph neural networks using model outputs
H Yang, X Yan, X Dai, Y Chen, J Cheng
IJCNN 2021, 2020
352020
Calibrating and Improving Graph Contrastive Learning
MA KAILI, Y Garry, H Yang, Y Chen, J Cheng
Transactions on Machine Learning Research (TMLR), 2023
15*2023
Towards Understanding Feature Learning in Out-of-Distribution Generalization
Y Chen*, W Huang*, K Zhou*, Y Bian, B Han, J Cheng
Advances in Neural Information Processing Systems (NeurIPS 2023), 2023
92023
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
Y Chen, Y Bian, K Zhou, B Xie, B Han, J Cheng
Advances in Neural Information Processing Systems (NeurIPS 2023), 2023
7*2023
Towards out-of-distribution generalizable predictions of chemical kinetics properties
Z Wang*, Y Chen*, Y Duan, W Li, B Han, J Cheng, H Tong
Oral presentation at NeurIPS 2023 workshop on AI for Science, 2023
42023
Dataset and Baseline System for Multi-lingual Extraction and Normalization of Temporal and Numerical Expressions
S Chen, Y Chen, BF Karlsson
Microsof Research Technical Report MSR-TR-2023-9, 2023
22023
Exact Shape Correspondence via 2D graph convolution
BF Kamhoua, L Zhang, Y Chen, H Yang, MA KAILI, B Han, B Li, J Cheng
Advances in Neural Information Processing Systems (NeurIPS 2022), 2022
2*2022
Do CLIPs Always Generalize Better than ImageNet Models?
Q Wang*, Y Lin*, Y Chen*, L Schmidt, B Han, T Zhang
arXiv preprint arXiv:2403.11497, 2024
2024
Discovery of the Hidden World with Large Language Models
C Liu*, Y Chen*, T Liu, M Gong, J Cheng, B Han, K Zhang
arXiv preprint arXiv:2402.03941, 2024
2024
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
B Xie, Y Bian, K Zhou, Y Chen, P Zhao, B Han, W Meng, J Cheng
International Conference on Learning Representations (ICLR 2024), 2024
2024
Enhancing Evolving Domain Generalization through Dynamic Latent Representations
B Xie, Y Chen, J Wang, K Zhou, B Han, W Meng, J Cheng
Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024) Oral …, 2024
2024
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes
Y Chen, B Xie, K Zhou, B Han, Y Bian, J Cheng
arXiv preprint arXiv:2311.18194, 2023
2023
Interpretable and Generalizable Graph Neural Networks via Subgraph Multilinear Extension
Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
Spotlight presentation at ICLR workshop Machine Learning for Genomics …, 2023
2023
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