Preprint, 2026 · Under submission

Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs

Colagrande, A., Caillon, P., Feillet, E., Allauzen, A.

arXiv · Code

AI & PDE Workshop at ICLR 2026

Limits of Resolution Equivariance in Fourier Neural Operators

Colagrande, A., Caillon, P., Feillet, E., Allauzen, A.

Paper

ICASSP 2026

Polynomial Mixing for Efficient Self-supervised Speech Recognition

Feillet, E., Whetten, R., Picard, D., Allauzen, A.

Paper · Code

ECLR Workshop at ICCV 2025

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics

Colagrande, A., Caillon, P., Feillet, E., Allauzen, A.

Paper · Code

Doctoral thesis, Université Paris-Saclay, 2024

Analysis and Recommendation Methods for Class-Incremental Learning

Feillet, E.

HAL

WACV 2025 · pp. 7614–7625

A Reality Check on Pre-training for Exemplar-free Class-Incremental Learning

Feillet, E., Popescu, A., & Hudelot, C.

Paper · Supplementary material

WACV 2025 · pp. 6932–6943

Temporal Dynamics in Visual Data: Analyzing the Impact of Time on Classification Accuracy

Pégeot, T., Feillet, E., Popescu, A., Kucher, I., & Delezoide, B.

Paper · Supplementary material · Data

ICPR 2024

Recommendation of Data-free Class-Incremental Learning Algorithms by Simulating Future Data

Feillet, E., Popescu, A., & Hudelot, C.

Paper · Supplementary material

WACV 2024 · pp. 1837–1847

An Analysis of Initial Training Strategies for Exemplar-free Class-Incremental Learning

Feillet, E., Petit, G., Soumm, M., Popescu, A., Delezoide, B., Picard, D., & Hudelot, C.

Paper · Supplementary material

WACV 2023 · pp. 2400–2409

AdvisIL — A Class-Incremental Learning Advisor

Feillet, E., Petit, G., Popescu, A., Reyboz, M., & Hudelot, C.

Paper · Supplementary material · Code

RFIAP 2022

Incremental Learning under Memory Constraints: A Scaling Heuristic for Deep Convolutional Models

Feillet, E., Petit, G., Popescu, A., Reyboz, M., & Hudelot, C.

Paper · Code