Danai Koutra
University of Michigan
H-index: 38
North America-United States
Top articles of Danai Koutra
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
5 Working Groups 5.1 Working Group on Causal Representation Learning | Scalable Graph Mining and Learning | Danai Koutra Henning Meyerhenke Ilya Safro | 2024/4 |
Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices | Jing Zhu Yuhang Zhou Vassilis N Ioannidis Shengyi Qian Wei Ai | 2024/3/4 | |
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks | arXiv preprint arXiv:2401.03350 | Puja Trivedi Mark Heimann Rushil Anirudh Danai Koutra Jayaraman J Thiagarajan | 2024/1/7 |
On performance discrepancies across local homophily levels in graph neural networks | Donald Loveland Jiong Zhu Mark Heimann Benjamin Fish Michael T Schaub | 2024/4/17 | |
Scalable Graph Mining and Learning (Dagstuhl Seminar 23491) | Danai Koutra Henning Meyerhenke Ilya Safro Fabian Brandt-Tumescheit | 2024 | |
On Estimating Link Prediction Uncertainty Using Stochastic Centering | Puja Trivedi Danai Koutra Jayaraman J Thiagarajan | 2024/4/14 | |
Leveraging Graph Diffusion Models for Network Refinement Tasks | arXiv preprint arXiv:2311.17856 | Puja Trivedi Ryan Rossi David Arbour Tong Yu Franck Dernoncourt | 2023/11/29 |
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023) | Jiaqi Ma Jiong Zhu Yuxiao Dong Danai Koutra Jingrui He | 2023/8/6 | |
A Stochastic Centering Framework for Improving Calibration in Graph Neural Networks | Puja Trivedi Mark Heimann Rushil Anirudh Danai Koutra Jayaraman J Thiagarajan | 2023/10/13 | |
SpotTarget: Rethinking the Effect of Target Edges for Link Prediction in Graph Neural Networks | arXiv preprint arXiv:2306.00899 | Jing Zhu Yuhang Zhou Vassilis N Ioannidis Shengyi Qian Wei Ai | 2023/6/1 |
Interpretable sparsification of brain graphs: Better practices and effective designs for graph neural networks | Gaotang Li Marlena Duda Xiang Zhang Danai Koutra Yujun Yan | 2023/8/6 | |
Simplifying distributed neural network training on massive graphs: Randomized partitions improve model aggregation | arXiv preprint arXiv:2305.09887 | Jiong Zhu Aishwarya Reganti Edward Huang Charles Dickens Nikhil Rao | 2023/5/17 |
Size Generalization of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective | Yujun Yan Gaotang Li Danai Koutra | 2023/10/13 | |
Unified Dense Subgraph Detection: Fast Spectral Theory based Algorithms | IEEE Transactions on Knowledge and Data Engineering | Wenjie Feng Shenghua Liu Danai Koutra Xueqi Cheng | 2023/7/17 |
A closer look at model adaptation using feature distortion and simplicity bias | arXiv preprint arXiv:2303.13500 | Puja Trivedi Danai Koutra Jayaraman J Thiagarajan | 2023/3/23 |
TouchUp-G: Improving feature representation through graph-centric finetuning | arXiv preprint arXiv:2309.13885 | Jing Zhu Xiang Song Vassilis N Ioannidis Danai Koutra Christos Faloutsos | 2023/9/25 |
Heterophily and graph neural networks: Past, present and future | IEEE Data Engineering Bulletin | Jiong Zhu Yujun Yan Mark Heimann Lingxiao Zhao Leman Akoglu | 2023/1 |
Graph coarsening via convolution matching for scalable graph neural network training | arXiv preprint arXiv:2312.15520 | Charles Dickens Eddie Huang Aishwarya Reganti Jiong Zhu Karthik Subbian | 2023/12/24 |
A provable framework of learning graph embeddings via summarization | Proceedings of the AAAI Conference on Artificial Intelligence | Houquan Zhou Shenghua Liu Danai Koutra Huawei Shen Xueqi Cheng | 2023/6/26 |
Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part V | Yasemin Altun Kamalika Das Taneli Mielikäinen Donato Malerba Jerzy Stefanowski | 2017/12/29 |
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