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Yatao A. Bian
Yatao A. Bian
Tencent AI Lab
Verified email at inf.ethz.ch - Homepage
Title
Cited by
Cited by
Year
Self-Supervised Graph Transformer on Large-Scale Molecular Data
Y Rong*, Y Bian*, T Xu, W Xie, Y Wei, W Huang, J Huang
Advances in Neural Information Processing Systems 33, 2020
4072020
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
AA Bian, JM Buhmann, A Krause, S Tschiatschek
ICML 2017, 2017
2482017
Guaranteed non-convex optimization: Submodular maximization over continuous domains
AA Bian, B Mirzasoleiman, JM Buhmann, A Krause
AISTATS 2017, 2017
1492017
CoLa: Communication-Efficient Decentralized Linear Learning
L He*, A Bian*, M Jaggi
NeurIPS 2018, 2018
126*2018
Independent SE (3)-Equivariant Models for End-to-End Rigid Protein Docking
OE Ganea, X Huang, C Bunne, Y Bian, R Barzilay, T Jaakkola, A Krause
ICLR 2022 Spotlight, 2021
862021
Continuous DR-submodular Maximization: Structure and Algorithms
A Bian, K Levy, A Krause, JM Buhmann
NIPS 2017, 486-496, 2017
812017
Graph Information Bottleneck for Subgraph Recognition
J Yu, T Xu, Y Rong, Y Bian, J Huang, R He
ICLR 2021, 2020
802020
Cross-dependent graph neural networks for molecular property prediction
H Ma, Y Bian, Y Rong, W Huang, T Xu, W Xie, G Ye, J Huang
Bioinformatics 38 (7), 2003-2009, 2022
68*2022
Transformer for graphs: An overview from architecture perspective
E Min, R Chen, Y Bian, T Xu, K Zhao, W Huang, P Zhao, J Huang, ...
arXiv preprint arXiv:2202.08455, 2022
412022
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference
YA Bian, JM Buhmann, A Krause
ICML, 644-653, 2019
37*2019
A Distributed Second-Order Algorithm You Can Trust
C DŁnner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi
ICML 2018, 2018
342018
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-aided Drug Discovery--A Focus on Affinity Prediction Problems with Noise Annotations
Y Ji, L Zhang, J Wu, B Wu, L Li, LK Huang, T Xu, Y Rong, J Ren, D Xue, ...
DataPerf Workshop at ICML 2022, 2022
31*2022
On Self-Distilling Graph Neural Network
Y Chen, Y Bian, X Xiao, Y Rong, T Xu, J Huang
IJCAI 2021, 2020
302020
Divide-and-conquer: Post-user interaction network for fake news detection on social media
E Min, Y Rong, Y Bian, T Xu, P Zhao, J Huang, S Ananiadou
Proceedings of the ACM Web Conference 2022, 1148-1158, 2022
272022
Recognizing Predictive Substructures with Subgraph Information Bottleneck
J Yu, T Xu, Y Rong, Y Bian, J Huang, R He
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
262021
Not all low-pass filters are robust in graph convolutional networks
H Chang, Y Rong, T Xu, Y Bian, S Zhou, X Wang, J Huang, W Zhu
Advances in Neural Information Processing Systems 34, 25058-25071, 2021
222021
Invariance Principle Meets Out-of-Distribution Generalization on Graphs
Y Chen, Y Zhang, Y Bian, H Yang, K Ma, B Xie, T Liu, B Han, J Cheng
ICML Workshop on Spurious Correlations, Invariance and Stability, 2022
202022
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
NeurIPS 2022 Spotlight, 2022
192022
Continuous submodular function maximization
Y Bian, JM Buhmann, A Krause
arXiv preprint arXiv:2006.13474, 2020
172020
Fine-tuning graph neural networks via graph topology induced optimal transport
J Zhang, X Xiao, LK Huang, Y Rong, Y Bian
IJCAI 2022, 2022
162022
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