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2020 – today
- 2024
[j2]Peng Liu
, Yasu Cao, Yujun Yan, Yong Wang:
Firmware Vulnerability Detection Algorithm Based on Matching Pattern-Specific Numerical Features With Structural Features. IEEE Access 12: 42317-42328 (2024)- [c12]Vipul Gupta, Xin Chen, Ruoyun Huang, Fanlong Meng, Jianjun Chen, Yujun Yan:
GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs. CIKM 2024: 4514-4521 - [c11]Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan:
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning. ICML 2024 - [c10]Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou:
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs. ICML 2024 - [i13]Yihe Wang, Nan Huang, Taida Li, Yujun Yan, Xiang Zhang:
Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification. CoRR abs/2405.19363 (2024) - [i12]Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan:
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning. CoRR abs/2406.04601 (2024) - [i11]Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang:
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance. CoRR abs/2407.12996 (2024) - [i10]Vipul Gupta, Xin Chen, Ruoyun Huang, Fanlong Meng, Jianjun Chen, Yujun Yan:
GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs. CoRR abs/2407.15452 (2024) - [i9]Yihe Wang, Taida Li, Yujun Yan, Wenzhan Song, Xiang Zhang:
How to evaluate your medical time series classification? CoRR abs/2410.03057 (2024) - 2023
- [j1]Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra:
Heterophily and Graph Neural Networks: Past, Present and Future. IEEE Data Eng. Bull. 46(2): 12-34 (2023) - [c9]Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan:
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. KDD 2023: 1223-1234 - [i8]Yujun Yan, Gaotang Li, Danai Koutra:
Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective. CoRR abs/2305.15611 (2023) - [i7]Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan:
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. CoRR abs/2306.14375 (2023) - 2022
- [c8]Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra:
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. ICDM 2022: 1287-1292 - [c7]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. WWW 2022: 1538-1549 - 2021
- [c6]Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang:
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks. 3DV 2021: 1331-1340 - [c5]Zhengming Zhang, Yaoqing Yang, Zhewei Yao, Yujun Yan, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models. IEEE BigData 2021: 1214-1225 - [i6]Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra:
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. CoRR abs/2102.06462 (2021) - [i5]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. CoRR abs/2111.03220 (2021) - [i4]Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang:
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks. CoRR abs/2111.15158 (2021) - 2020
- [c4]Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi:
Neural Execution Engines: Learning to Execute Subroutines. NeurIPS 2020 - [c3]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. NeurIPS 2020 - [i3]Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi:
Neural Execution Engines: Learning to Execute Subroutines. CoRR abs/2006.08084 (2020) - [i2]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Generalizing Graph Neural Networks Beyond Homophily. CoRR abs/2006.11468 (2020) - [i1]Zhengming Zhang, Zhewei Yao, Yaoqing Yang, Yujun Yan, Joseph E. Gonzalez, Michael W. Mahoney:
Benchmarking Semi-supervised Federated Learning. CoRR abs/2008.11364 (2020)
2010 – 2019
- 2019
- [c2]Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra:
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. KDD 2019: 772-782 - 2018
- [c1]Yujun Yan, Mark Heimann, Di Jin, Danai Koutra:
Fast Flow-based Random Walk with Restart in a Multi-query Setting. SDM 2018: 342-350
Coauthor Index
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last updated on 2024-11-15 20:39 CET by the dblp team
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