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Guillermo Ortiz-Jiménez
Guillermo Ortiz-Jiménez
Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
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
582020
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
572021
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
522020
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
402023
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
382021
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
362021
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
362019
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
282018
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
222017
On the benefits of knowledge distillation for adversarial robustness
J Maroto, G Ortiz-Jiménez, P Frossard
arXiv preprint arXiv:2203.07159, 2022
202022
Neural Anisotropy Directions
G Ortiz-Jimenez*, A Modas*, SM Moosavi-Dezfooli, P Frossard
Advances in Neural Information Processing Systems (NeurIPS), 2020
162020
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
112020
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
72021
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
52023
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
4*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
42020
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
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