| On the Role of Neural Collapse in Transfer Learning T Galanti, A György, M Hutter International Conference on Learning Representations (ICLR), 2021 | 126 | 2021 |
| Image2point: 3d point-cloud understanding with 2d image pretrained models C Xu, S Yang, T Galanti, B Wu, X Yue, B Zhai, W Zhan, P Vajda, K Keutzer, ... European Conference on Computer Vision, 638-656, 2022 | 115* | 2022 |
| On the Modularity of Hypernetworks T Galanti, L Wolf Advances in Neural Information Processing Systems 33, 10409-10419, 2020 | 98 | 2020 |
| Evaluation metrics for conditional image generation Y Benny, T Galanti, S Benaim, L Wolf International Journal of Computer Vision 129 (5), 1712-1731, 2021 | 76 | 2021 |
| Feature learning in deep classifiers through intermediate neural collapse A Rangamani, M Lindegaard, T Galanti, TA Poggio International conference on machine learning, 28729-28745, 2023 | 74 | 2023 |
| SGD with weight decay secretly minimizes the ranks of your neural networks T Galanti, ZS Siegel, A Gupte, TA Poggio The Second Conference on Parsimony and Learning (Proceedings Track), 2025 | 60* | 2025 |
| Dynamics in deep classifiers trained with the square loss: Normalization, low rank, neural collapse, and generalization bounds M Xu, A Rangamani, Q Liao, T Galanti, T Poggio Research 6, 0024, 2023 | 54* | 2023 |
| Reverse engineering self-supervised learning I Ben-Shaul, R Shwartz-Ziv, T Galanti, S Dekel, Y LeCun Advances in Neural Information Processing Systems 36, 58324-58345, 2023 | 51 | 2023 |
| Emerging Disentanglement in Auto-Encoder based Unsupervised Image Content Transfer O Press, T Galanti, S Benaim, L Wolf International Conference on Learning Representations (ICLR), 2018 | 48 | 2018 |
| A Theoretical Framework for Deep Transfer Learning T Galanti, L Wolf, T Hazan Information and Inference: A Journal of the IMA 5 (2), 159-209, 2016 | 45 | 2016 |
| On infinite-width hypernetworks E Littwin, T Galanti, L Wolf, G Yang Advances in neural information processing systems 33, 13226-13237, 2020 | 37* | 2020 |
| A Formal Approach to Explainability L Wolf, T Galanti, T Hazan AAAI/ACM Conference on Artificial Intelligence, Ethics and Society 2, 2019 | 33 | 2019 |
| Domain Intersection and Domain Difference S Benaim, M Khaitov, T Galanti, L Wolf Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 30 | 2019 |
| On the Implicit Bias Towards Minimal Depth of Deep Neural Networks T Galanti, L Galanti, I Ben-Shaul arXiv preprint arXiv:2202.09028, 2022 | 29* | 2022 |
| The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings T Galanti, L Wolf, S Benaim International Conference on Learning Representations (ICLR), 2017 | 29* | 2017 |
| Norm-based generalization bounds for sparse neural networks T Galanti, M Xu, L Galanti, T Poggio Advances in Neural Information Processing Systems 36, 42482-42501, 2023 | 26* | 2023 |
| Generalization bounds for transfer learning with pretrained classifiers T Galanti, A György, M Hutter CoRR, 2022 | 22 | 2022 |
| Improved Generalization Bounds for Transfer Learning via Neural Collapse T Galanti, A György, M Hutter First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at …, 2022 | 20 | 2022 |
| Formation of representations in neural networks L Ziyin, I Chuang, T Galanti, T Poggio arXiv preprint arXiv:2410.03006, 2024 | 14* | 2024 |
| Estimating the success of unsupervised image to image translation S Benaim*, T Galanti*, L Wolf, (*equal contributions) Proceedings of the European Conference on Computer Vision (ECCV), 218-233, 2018 | 13 | 2018 |
Lior WolfThe School of Computer Science at Tel Aviv UniversityVerified email at cs.tau.ac.il
