| A note on over-smoothing for graph neural networks C Cai, Y Wang arXiv preprint arXiv:2006.13318, 2020 | 402 | 2020 |
| Computational topology for data analysis TK Dey, Y Wang Cambridge University Press, 2022 | 375 | 2022 |
| Discrete Laplace operator on meshed surfaces M Belkin, J Sun, Y Wang Proceedings of the twenty-fourth annual symposium on Computational geometry …, 2008 | 305 | 2008 |
| Constructing Laplace Operator from Point Clouds in ℝd M Belkin, J Sun, Y Wang Proceedings of the twentieth annual ACM-SIAM symposium on Discrete …, 2009 | 257 | 2009 |
| Fréchet distance for curves, revisited B Aronov, S Har-Peled, C Knauer, Y Wang, C Wenk European symposium on algorithms, 52-63, 2006 | 219 | 2006 |
| Near-linear time approximation algorithms for curve simplification PK Agarwal, S Har-Peled, NH Mustafa, Y Wang Algorithmica 42 (3), 203-219, 2005 | 203 | 2005 |
| Extreme elevation on a 2-manifold PK Agarwal, H Edelsbrunner, J Harer, Y Wang Proceedings of the twentieth annual symposium on Computational geometry, 357-365, 2004 | 189 | 2004 |
| Computing topological persistence for simplicial maps TK Dey, F Fan, Y Wang Proceedings of the thirtieth annual symposium on Computational geometry, 345-354, 2014 | 174 | 2014 |
| A topological regularizer for classifiers via persistent homology C Chen, X Ni, Q Bai, Y Wang The 22nd international conference on artificial intelligence and statistics …, 2019 | 166 | 2019 |
| Learning metrics for persistence-based summaries and applications for graph classification Q Zhao, Y Wang Advances in neural information processing systems 32, 2019 | 156 | 2019 |
| A simple yet effective baseline for non-attributed graph classification C Cai, Y Wang arXiv preprint arXiv:1811.03508, 2018 | 154 | 2018 |
| Persistent heat signature for pose‐oblivious matching of incomplete models TK Dey, K Li, C Luo, P Ranjan, I Safa, Y Wang Computer Graphics Forum 29 (5), 1545-1554, 2010 | 151 | 2010 |
| Measuring distance between Reeb graphs U Bauer, X Ge, Y Wang Proceedings of the thirtieth annual symposium on Computational geometry, 464-473, 2014 | 149 | 2014 |
| Data skeletonization via Reeb graphs X Ge, I Safa, M Belkin, Y Wang Advances in neural information processing systems 24, 2011 | 141 | 2011 |
| Exact algorithms for partial curve matching via the Fréchet distance K Buchin, M Buchin, Y Wang Proceedings of the twentieth annual ACM-SIAM symposium on Discrete …, 2009 | 141 | 2009 |
| Understanding oversquashing in gnns through the lens of effective resistance M Black, Z Wan, A Nayyeri, Y Wang International Conference on Machine Learning, 2528-2547, 2023 | 134 | 2023 |
| Graph coarsening with neural networks C Cai, D Wang, Y Wang arXiv preprint arXiv:2102.01350, 2021 | 128 | 2021 |
| Unperturbed: spectral analysis beyond Davis-Kahan J Eldridge, M Belkin, Y Wang Algorithmic learning theory, 321-358, 2018 | 128 | 2018 |
| Topology-aware segmentation using discrete morse theory X Hu, Y Wang, L Fuxin, D Samaras, C Chen arXiv preprint arXiv:2103.09992, 2021 | 125 | 2021 |
| Persistence enhanced graph neural network Q Zhao, Z Ye, C Chen, Y Wang International Conference on Artificial Intelligence and Statistics, 2896-2906, 2020 | 117 | 2020 |
Tamal K. DeyProfessor Computer Science, Purdue UniversityVerified email at purdue.edu
