PhD student @ EPFL🇨🇭 . Interested in understanding why ML works and why ML fails.
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tml-epfl/understanding-sam Public
Towards Understanding Sharpness-Aware Minimization [ICML 2022]
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On the effectiveness of adversarial training against common corruptions [UAI 2022]
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RobustBench/robustbench Public
RobustBench: a standardized adversarial robustness benchmark [NeurIPS'21 Benchmarks and Datasets Track]
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Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
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square-attack Public
Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]
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provably-robust-boosting Public
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]



