Yujun Yan

According to our database, Yujun Yan authored at least 22 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks.

Xuyuan Liu, Yinghao Cai, Qihui Yang, Yujun Yan

CoRR, 2024

How to evaluate your medical time series classification?

Yihe Wang, Taida Li, Yujun Yan, Wenzhan Song, Xiang Zhang

CoRR, 2024

GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs.

Vipul Gupta, Xin Chen, Ruoyun Huang, Fanlong Meng, Jianjun Chen, Yujun Yan

CoRR, 2024

Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance.

Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang

CoRR, 2024

Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification.

Yihe Wang, Nan Huang, Taida Li, Yujun Yan, Xiang Zhang

CoRR, 2024

Firmware Vulnerability Detection Algorithm Based on Matching Pattern-Specific Numerical Features With Structural Features.

Peng Liu, Yasu Cao, Yujun Yan, Yong Wang

IEEE Access, 2024

EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs.

Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning.

Zheng Huang, Qihui Yang, Dawei Zhou, Yujun Yan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs.

Vipul Gupta, Xin Chen, Ruoyun Huang, Fanlong Meng, Jianjun Chen, Yujun Yan

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Heterophily and Graph Neural Networks: Past, Present and Future.

Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra

IEEE Data Eng. Bull., 2023

Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective.

Yujun Yan, Gaotang Li, Danai Koutra

CoRR, 2023

Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks.

Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices.

Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks.

Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models.

Zhengming Zhang, Yaoqing Yang, Zhewei Yao, Yujun Yan, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks.

Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang

Proceedings of the International Conference on 3D Vision, 2021

2020

Benchmarking Semi-supervised Federated Learning.

Zhengming Zhang, Zhewei Yao, Yaoqing Yang, Yujun Yan, Joseph E. Gonzalez, Michael W. Mahoney

CoRR, 2020

Generalizing Graph Neural Networks Beyond Homophily.

Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra

CoRR, 2020

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs.

Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Neural Execution Engines: Learning to Execute Subroutines.

Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data.

Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Fast Flow-based Random Walk with Restart in a Multi-query Setting.

Yujun Yan, Mark Heimann, Di Jin, Danai Koutra

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018