Scalable Lipschitz Residual Networks with Convex Potential Flows. - Laurent Meunier; Blaise Delattre; Alexandre Araujo; Alexandre Allauzen (CoRR, 2021)

A Dynamical System Perspective for Lipschitz Neural Networks. - Laurent Meunier; Blaise Delattre; Alexandre Araujo; Alexandre Allauzen (ICML, 2022)

A Unified Algebraic Perspective on Lipschitz Neural Networks. - Alexandre Araujo; Aaron J. Havens; Blaise Delattre; Alexandre Allauzen; Bin Hu 002 (ICLR, 2023)

Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration. - Blaise Delattre; Quentin Barthélemy; Alexandre Araujo; Alexandre Allauzen (ICML, 2023)

Chain and Causal Attention for Efficient Entity Tracking. - Erwan Fagnou; Paul Caillon; Blaise Delattre; Alexandre Allauzen (EMNLP, 2024)

The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing. - Blaise Delattre; Alexandre Araujo; Quentin Barthélemy; Alexandre Allauzen (ICLR, 2024)

Spectral Norm of Convolutional Layers with Circular and Zero Paddings. - Blaise Delattre; Quentin Barthélemy; Alexandre Allauzen (CoRR, 2024)

Bridging the Theoretical Gap in Randomized Smoothing. - Blaise Delattre; Paul Caillon; Quentin Barthélemy; Erwan Fagnou; Alexandre Allauzen (AISTATS, 2025)

Accelerated training through iterative gradient propagation along the residual path. - Erwan Fagnou; Paul Caillon; Blaise Delattre; Alexandre Allauzen (ICLR, 2025)

Conditional Distribution Quantization in Machine Learning. - Blaise Delattre; Sylvain Delattre; Alexandre Verine; Alexandre Allauzen (CoRR, 2025)