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Victor Bouvier
Victor Bouvier
Suez Data & AI (Digital Solutions)
Bestätigte E-Mail-Adresse bei suez.com
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Zitiert von
Zitiert von
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Efficient parallel generation of random field of mechanical properties for geophysical application
L Paludo, V Bouvier, R Cottereau, D Clouteau
6th International Conference on Earthquake Geotechnical Engineering, 2015
24*2015
Bridging few-shot learning and adaptation: new challenges of support-query shift
E Bennequin, V Bouvier, M Tami, A Toubhans, C Hudelot
Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021
182021
Robust domain adaptation: Representations, weights and inductive bias
V Bouvier, P Very, C Chastagnol, M Tami, C Hudelot
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021
142021
Hidden covariate shift: A minimal assumption for domain adaptation
V Bouvier, P Very, C Hudelot, C Chastagnol
arXiv preprint arXiv:1907.12299, 2019
112019
Performance prediction under dataset shift
S Maggio, V Bouvier, L Dreyfus-Schmidt
2022 26th International Conference on Pattern Recognition (ICPR), 2466-2474, 2022
52022
Target consistency for domain adaptation: when robustness meets transferability
Y Ouali, V Bouvier, M Tami, C Hudelot
arXiv preprint arXiv:2006.14263, 2020
42020
Domain-invariant representations: A look on compression and weights
V Bouvier, C Hudelot, C Chastagnol, P Very, M Tami
32019
Stochastic adversarial gradient embedding for active domain adaptation
V Bouvier, P Very, C Chastagnol, M Tami, C Hudelot
arXiv preprint arXiv:2012.01843, 2020
22020
Test-Time Adaptation with Principal Component Analysis
T Cordier, V Bouvier, G Hénaff, C Hudelot
arXiv preprint arXiv:2209.05779, 2022
12022
Towards clear expectations for uncertainty estimation
V Bouvier, S Maggio, A Abraham, L Dreyfus-Schmidt
arXiv preprint arXiv:2207.13341, 2022
12022
Towards Adaptive Learning with Invariant Representations
V Bouvier
Université Paris-Saclay, 2021
2021
Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets
V Bouvier, P Very, C Hudelot, C Chastagnol
arXiv preprint arXiv:1907.12305, 2019
2019
Adversarial Word Embeddings to Improve Text Classifiers Generalization Power
V Bouvier, C Hudelot, P Very
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