| Imbalance trouble: Revisiting neural-collapse geometry C Thrampoulidis, GR Kini, V Vakilian, T Behnia Advances in Neural Information Processing Systems 35, 27225-27238, 2022 | 44 | 2022 |
| On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data T Behnia, GR Kini, V Vakilian, C Thrampoulidis International Conference on Artificial Intelligence and Statistics, 10815-10838, 2023 | 14 | 2023 |
| Supervised-Contrastive Loss Learns Orthogonal Frames and Batching Matters GR Kini, V Vakilian, T Behnia, J Gill, C Thrampoulidis arXiv preprint arXiv:2306.07960, 2023 | 5 | 2023 |
| On how to avoid exacerbating spurious correlations when models are overparameterized T Behnia, K Wang, C Thrampoulidis 2022 IEEE International Symposium on Information Theory (ISIT), 121-126, 2022 | 2 | 2022 |
| Supervised Contrastive Representation Learning: Landscape Analysis with Unconstrained Features T Behnia, C Thrampoulidis arXiv preprint arXiv:2402.18884, 2024 | | 2024 |
| Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching GR Kini, V Vakilian, T Behnia, J Gill, C Thrampoulidis The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
| Learning from imbalanced data: a geometric study on over-parameterized models T Behnia University of British Columbia, 2023 | | 2023 |
