Hidden Covariate Shift: A Minimal Assumption For Domain Adaptation. - Victor Bouvier; Philippe Very; Céline Hudelot; Clément Chastagnol (CoRR, 2019)

Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets. - Victor Bouvier; Philippe Very; Céline Hudelot; Clément Chastagnol (CoRR, 2019)

Robust Domain Adaptation: Representations, Weights and Inductive Bias. - Victor Bouvier; Philippe Very; Clément Chastagnol; Myriam Tami; Céline Hudelot (ECML/PKDD (1), 2020)

Target Consistency for Domain Adaptation: when Robustness meets Transferability. - Yassine Ouali; Victor Bouvier; Myriam Tami; Céline Hudelot (CoRR, 2020)

Robust Domain Adaptation: Representations, Weights and Inductive Bias (Extended Abstract). - Victor Bouvier; Philippe Very; Clément Chastagnol; Myriam Tami; Céline Hudelot (IJCAI, 2021)

Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift. - Etienne Bennequin; Victor Bouvier; Myriam Tami; Antoine Toubhans; Céline Hudelot (ECML/PKDD (1), 2021)

Stochastic Adversarial Gradient Embedding for Active Domain Adaptation. - Victor Bouvier; Philippe Very; Clément Chastagnol; Myriam Tami; Céline Hudelot (IAL@PKDD/ECML, 2021)

Towards Adaptive Learning with Invariant Representations. (Vers l'apprentissage adaptatif avec des représentations invariantes). - Victor Bouvier (2021)

Performance Prediction Under Dataset Shift. - Simona Maggio; Victor Bouvier; Léo Dreyfus-Schmidt (ICPR, 2022)

Towards Clear Expectations for Uncertainty Estimation. - Victor Bouvier; Simona Maggio; Alexandre Abraham; Léo Dreyfus-Schmidt (CoRR, 2022)

Test-Time Adaptation with Principal Component Analysis. - Thomas Cordier; Victor Bouvier; Gilles Hénaff; Céline Hudelot (CoRR, 2022)