| Square attack: a query-efficient black-box adversarial attack via random search M Andriushchenko*, F Croce*, N Flammarion, M Hein ECCV 2020, 2020 | 728 | 2020 |
| Formal guarantees on the robustness of a classifier against adversarial manipulation M Hein, M Andriushchenko NeurIPS 2017, 2017 | 530 | 2017 |
| Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem M Hein, M Andriushchenko, J Bitterwolf CVPR 2019 (oral), 2019 | 486 | 2019 |
| RobustBench: a standardized adversarial robustness benchmark F Croce*, M Andriushchenko*, V Sehwag*, E Debenedetti*, N Flammarion, ... NeurIPS 2021 Datasets and Benchmarks Track, Best Paper Honorable Mention …, 2021 | 427 | 2021 |
| On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines M Mosbach, M Andriushchenko, D Klakow ICLR 2021, 2021 | 305 | 2021 |
| Understanding and Improving Fast Adversarial Training M Andriushchenko, N Flammarion NeurIPS 2020, 2020 | 229 | 2020 |
| Provable Robustness of ReLU Networks via Maximization of Linear Regions F Croce*, M Andriushchenko*, M Hein AISTATS 2019, 2019 | 174 | 2019 |
| On the effectiveness of adversarial training against common corruptions K Kireev*, M Andriushchenko*, N Flammarion UAI 2022, 2021 | 79 | 2021 |
| Towards Understanding Sharpness-Aware Minimization M Andriushchenko, N Flammarion ICML 2022, 2022 | 70 | 2022 |
| Logit Pairing Methods Can Fool Gradient-Based Attacks M Mosbach*, M Andriushchenko*, T Trost, M Hein, D Klakow NeurIPS 2018 Workshop on Security in Machine Learning, 2018 | 69 | 2018 |
| Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks F Croce, M Andriushchenko, ND Singh, N Flammarion, M Hein AAAI 2022, 2022 | 63 | 2022 |
| Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks M Andriushchenko, M Hein NeurIPS 2019, 2019 | 63 | 2019 |
| SGD with Large Step Sizes Learns Sparse Features M Andriushchenko, A Varre, L Pillaud-Vivien, N Flammarion ICML 2023, 2022 | 26 | 2022 |
| A Modern Look at the Relationship between Sharpness and Generalization M Andriushchenko, F Croce, M Müller, M Hein, N Flammarion ICML 2023, 2023 | 10 | 2023 |
| #ScienceForUkraine: an Initiative to Support the Ukrainian Academic Community. “3 Months Since Russia’s Invasion in Ukraine”, February 26 – May 31, 2022 M Rose, S Reinsone, M Andriushchenko, M Bartosiak, A Bobak, L Drury, ... Available at SSRN: https://ssrn.com/abstract=4139263, 2022 | 5 | 2022 |
| Sharpness-Aware Minimization Leads to Low-Rank Features M Andriushchenko, D Bahri, H Mobahi, N Flammarion NeurIPS 2023, 2023 | 2 | 2023 |
| Why Do We Need Weight Decay in Modern Deep Learning? M Andriushchenko*, F D'Angelo*, A Varre, N Flammarion arXiv:2310.04415 & NeurIPS 2023 Workshop on Mathematics of Modern ML, 2023 | | 2023 |
| Layerwise Linear Mode Connectivity L Adilova, M Andriushchenko, M Kamp, A Fischer, M Jaggi arXiv:2307.06966 & ICML 2023 Workshop on High-dimensional Learning Dynamics, 2023 | | 2023 |
| Adversarially robust visual fingerprinting and image provenance models M Andriushchenko, J Collomosse, X Li, G Oxholm US Patent App. 17/573,041, 2023 | | 2023 |
| Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings K Kireev, M Andriushchenko, C Troncoso, N Flammarion NeurIPS 2023, 2023 | | 2023 |
Nicolas FlammarionEPFLVerified email at epfl.ch
