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 | 56 | 2020 |
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 | 54 | 2021 |
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 | 50 | 2020 |
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 | 35 | 2019 |
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 | 34 | 2021 |
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 | 33 | 2021 |
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 | 30 | 2023 |
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 | 27 | 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 | 24* | 2019 |
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 | 21 | 2017 |
On the benefits of knowledge distillation for adversarial robustness J Maroto, G Ortiz-Jiménez, P Frossard arXiv preprint arXiv:2203.07159, 2022 | 19 | 2022 |
Neural Anisotropy Directions G Ortiz-Jimenez*, A Modas*, SM Moosavi-Dezfooli, P Frossard Advances in Neural Information Processing Systems (NeurIPS), 2020 | 15 | 2020 |
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 |
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 |
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 | 5 | 2023 |
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 |
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 | 3* | 2023 |
Multidomain Graph Signal Processing: Learning and Sampling (MSc. Thesis) G Ortiz-Jiménez Delft University of Technology, 2018 | 1* | 2018 |
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 | | 2024 |
Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels K Wang, G Ortiz-Jimenez, R Jenatton, M Collier, E Kokiopoulou, ... International Conference on Machine Learning (ICML), 2024 | | 2024 |