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Pascal Vincent
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Publications
- 2023
- [c67]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR 2023 - [c66]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. ICLR 2023 - [c65]Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. NeurIPS 2023 - [i51]Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari S. Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. CoRR abs/2308.03977 (2023) - [i50]Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering environments with XRM. CoRR abs/2309.16748 (2023) - [i48]Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim:
Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations. CoRR abs/2311.08815 (2023) - 2022
- [i43]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. CoRR abs/2210.07347 (2022) - [i42]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR abs/2211.01866 (2022)
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