| On the benefits of knowledge distillation for adversarial robustness J Maroto, G Ortiz-Jiménez, P Frossard arXiv preprint arXiv:2203.07159, 2022 | 18 | 2022 |
| SafeAMC: Adversarial training for robust modulation recognition models J Maroto, G Bovet, P Frossard arXiv preprint arXiv:2105.13746, 2021 | 7 | 2021 |
| Adversarial training with informed data selection MOK Mendonça, J Maroto, P Frossard, PSR Diniz 2022 30th European Signal Processing Conference (EUSIPCO), 608-612, 2022 | 4 | 2022 |
| On the benefits of robust models in modulation recognition J Maroto, G Bovet, P Frossard Artificial Intelligence and Machine Learning for Multi-Domain Operations …, 2021 | 4 | 2021 |
| Maximum Likelihood Distillation for Robust Modulation Classification J Maroto, G Bovet, P Frossard ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 3 | 2023 |
| Efficient worker assignment in crowdsourced data labeling using graph signal processing J Maroto, A Ortega 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 3 | 2018 |
| SafeAMC: Adversarial training for robust modulation classification models J Maroto, G Bovet, P Frossard 2022 30th European Signal Processing Conference (EUSIPCO), 1636-1640, 2022 | 2 | 2022 |
| Modurec: Recommender systems with feature and time modulation J Maroto, C Vignac, P Frossard ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 1 | 2021 |
| Active learning in Crowdsourcing classification problems using Sampling Theory for graph signals JA Maroto Morales Universitat Politècnica de Catalunya, 2017 | | 2017 |
| Active Learning in Crowdsourcing Classification Problems Using Sampling Theory for Graph Signals JAM Morales Universitat Politècnica de Catalunya. Escola Tècnica Superior d'Enginyeria …, 2017 | | 2017 |
