| Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models G Ortiz-Jimenez*, A Favero*, P Frossard Advances in Neural Information Processing Systems (NeurIPS) - Oral presentation, 2023 | 79 | 2023 |
| A Structured Dictionary Perspective on Implicit Neural Representations G Yüce*, G Ortiz-Jiménez*, B Besbinar, P Frossard IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 76 | 2021 |
| Optimism in the face of adversity: Understanding and improving deep learning through adversarial robustness G Ortiz-Jiménez, A Modas, SM Moosavi-Dezfooli, P Frossard Proceedings of the IEEE 109 (5), 2020 | 60 | 2020 |
| Hold me tight! Influence of discriminative features on deep network boundaries G Ortiz-Jimenez*, A Modas*, SM Moosavi-Dezfooli, P Frossard Advances in Neural Information Processing Systems (NeurIPS), 2020 | 55 | 2020 |
| What can linearized neural networks actually say about generalization? G Ortiz-Jiménez, SM Moosavi-Dezfooli, P Frossard Advances in Neural Information Processing Systems (NeurIPS), 2021 | 46 | 2021 |
| PRIME: A Few Primitives Can Boost Robustness to Common Corruptions A Modas*, R Rade*, G Ortiz-Jiménez, SM Moosavi-Dezfooli, P Frossard European Conference on Computer Vision (ECCV), 2021 | 45 | 2021 |
| Sparse sampling for inverse problems with tensors G Ortiz-Jiménez, M Coutino, SP Chepuri, G Leus IEEE Transactions on Signal Processing 67 (12), 3272-3286, 2019 | 36 | 2019 |
| Sampling and reconstruction of signals on product graphs G Ortiz-Jiménez, M Coutino, SP Chepuri, G Leus IEEE Global Conference on Signal and Information Processing (GlobalSIP), 713-717, 2018 | 30 | 2018 |
| CDOT: Continuous Domain Adaptation using Optimal Transport G Ortiz-Jimenez, ME Gheche, E Simou, HP Maretic, P Frossard Optimal Transport & Machine Learning Workshop (NeurIPS 2019), 2019 | 28* | 2019 |
| On the benefits of knowledge distillation for adversarial robustness J Maroto, G Ortiz-Jiménez, P Frossard arXiv preprint arXiv:2203.07159, 2022 | 27 | 2022 |
| Simulation Framework for a 3-D High-Resolution Imaging Radar at 300 GHz with a Scattering Model Based on Rendering Techniques G Ortiz-Jiménez, F García-Rial, LA Ubeda-Medina, R Pagés, N García, ... IEEE Transactions on Terahertz Science and Technology 7 (4), 404-414, 2017 | 23 | 2017 |
| Neural Anisotropy Directions G Ortiz-Jimenez*, A Modas*, SM Moosavi-Dezfooli, P Frossard Advances in Neural Information Processing Systems (NeurIPS), 2020 | 19 | 2020 |
| Localizing Task Information for Improved Model Merging and Compression K Wang, N Dimitriadis, G Ortiz-Jimenez, F Fleuret, P Frossard International Conference on Machine Learning (ICML), 2024 | 12 | 2024 |
| On the choice of graph neural network architectures C Vignac, G Ortiz-Jiménez, P Frossard ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 11 | 2020 |
| When does Privileged Information Explain Away Label Noise? G Ortiz-Jimenez*, M Collier*, A Nawalgaria, A D'Amour, J Berent, ... International Conference on Machine Learning (ICML), 2023 | 10 | 2023 |
| Ununlearning: Unlearning is not sufficient for content regulation in advanced generative ai I Shumailov, J Hayes, E Triantafillou, G Ortiz-Jimenez, N Papernot, ... arXiv preprint arXiv:2407.00106, 2024 | 9 | 2024 |
| Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, K Chan, Y Chen, ... arXiv preprint arXiv:2408.07009, 2024 | 7 | 2024 |
| Catastrophic overfitting can be induced with discriminative non-robust features G Ortiz-Jimenez, P de Jorge, A Sanyal, A Bibi, PK Dokania, P Frossard, ... Transactions on Machine Learning Research (TMLR), 2023 | 7* | 2023 |
| A neural anisotropic view of underspecification in deep learning G Ortiz-Jimenez, IF Salazar-Reque, A Modas, SM Moosavi-Dezfooli, ... RobustML Workshop (ICLR 2021), 2021 | 7 | 2021 |
| Redundant features can hurt robustness to distribution shift G Ortiz-Jiménez*, A Modas*, SM Moosavi-Dezfooli, P Frossard Uncertainty & Robustness in Deep Learning Workshop (ICML 2020), 2020 | 4 | 2020 |
Pascal FrossardEcole Polytechnique Fédérale de Lausanne, EPFLVerified email at epfl.ch
