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ORCIDSylvestre-Alvise Rebuffi
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2020 – today
- 2023
[j2]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. J. Mach. Learn. Res. 24: 308:1-308:77 (2023)- [c13]Francesco Croce, Sylvestre-Alvise Rebuffi, Evan Shelhamer, Sven Gowal:
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts. CVPR 2023: 12313-12323 - [c12]Sylvestre-Alvise Rebuffi, Francesco Croce, Sven Gowal:
Revisiting adapters with adversarial training. ICLR 2023 - [i18]Francesco Croce, Sylvestre-Alvise Rebuffi, Evan Shelhamer, Sven Gowal:
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts. CoRR abs/2302.10164 (2023) - [i17]Ira Ktena, Olivia Wiles, Isabela Albuquerque, Sylvestre-Alvise Rebuffi, Ryutaro Tanno, Abhijit Guha Roy, Shekoofeh Azizi, Danielle Belgrave, Pushmeet Kohli, Alan Karthikesalingam, A. Taylan Cemgil, Sven Gowal:
Generative models improve fairness of medical classifiers under distribution shifts. CoRR abs/2304.09218 (2023) - 2022
- [j1]Kai Han
, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
AutoNovel: Automatically Discovering and Learning Novel Visual Categories. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6767-6781 (2022) - [c11]Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal:
Defending Against Image Corruptions Through Adversarial Augmentations. ICLR 2022 - [c10]Olivia Wiles, Sven Gowal, Florian Stimberg, Sylvestre-Alvise Rebuffi, Ira Ktena, Krishnamurthy Dvijotham, Ali Taylan Cemgil:
A Fine-Grained Analysis on Distribution Shift. ICLR 2022 - [i16]Sylvestre-Alvise Rebuffi, Francesco Croce, Sven Gowal:
Revisiting adapters with adversarial training. CoRR abs/2210.04886 (2022) - [i15]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuang Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. CoRR abs/2211.11747 (2022) - 2021
- [c9]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
LSD-C: Linearly Separable Deep Clusters. ICCVW 2021: 1038-1046 - [c8]Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann:
Improving Robustness using Generated Data. NeurIPS 2021: 4218-4233 - [c7]Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Data Augmentation Can Improve Robustness. NeurIPS 2021: 29935-29948 - [i14]Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Fixing Data Augmentation to Improve Adversarial Robustness. CoRR abs/2103.01946 (2021) - [i13]Dan A. Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal:
Defending Against Image Corruptions Through Adversarial Augmentations. CoRR abs/2104.01086 (2021) - [i12]Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
AutoNovel: Automatically Discovering and Learning Novel Visual Categories. CoRR abs/2106.15252 (2021) - [i11]Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann:
Improving Robustness using Generated Data. CoRR abs/2110.09468 (2021) - [i10]Olivia Wiles, Sven Gowal, Florian Stimberg, Sylvestre-Alvise Rebuffi, Ira Ktena, Krishnamurthy Dvijotham, A. Taylan Cemgil:
A Fine-Grained Analysis on Distribution Shift. CoRR abs/2110.11328 (2021) - [i9]Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Data Augmentation Can Improve Robustness. CoRR abs/2111.05328 (2021) - 2020
- [b1]Sylvestre-Alvise Rebuffi:
Influence of the input data on learning deep representations. University of Oxford, UK, 2020 - [c6]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Semi-Supervised Learning with Scarce Annotations. CVPR Workshops 2020: 3294-3302 - [c5]Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi:
There and Back Again: Revisiting Backpropagation Saliency Methods. CVPR 2020: 8836-8845 - [c4]Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
Automatically Discovering and Learning New Visual Categories with Ranking Statistics. ICLR 2020 - [i8]Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
Automatically Discovering and Learning New Visual Categories with Ranking Statistics. CoRR abs/2002.05714 (2020) - [i7]Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi:
There and Back Again: Revisiting Backpropagation Saliency Methods. CoRR abs/2004.02866 (2020) - [i6]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
LSD-C: Linearly Separable Deep Clusters. CoRR abs/2006.10039 (2020)
2010 – 2019
- 2019
- [i5]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Semi-Supervised Learning with Scarce Annotations. CoRR abs/1905.08845 (2019) - [i4]Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Hakan Bilen, Andrea Vedaldi:
NormGrad: Finding the Pixels that Matter for Training. CoRR abs/1910.08823 (2019) - 2018
- [c3]Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi:
Efficient Parametrization of Multi-Domain Deep Neural Networks. CVPR 2018: 8119-8127 - [i3]Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi:
Efficient parametrization of multi-domain deep neural networks. CoRR abs/1803.10082 (2018) - 2017
- [c2]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CVPR 2017: 5533-5542 - [c1]Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi:
Learning multiple visual domains with residual adapters. NIPS 2017: 506-516 - [i2]Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi:
Learning multiple visual domains with residual adapters. CoRR abs/1705.08045 (2017) - 2016
- [i1]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CoRR abs/1611.07725 (2016)
Coauthor Index
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