Regularized spectral methods for clustering signed networks. - Mihai Cucuringu; Apoorv Vikram Singh; Déborah Sulem; Hemant Tyagi (J. Mach. Learn. Res., 2021)

Diverse Counterfactual Explanations for Anomaly Detection in Time Series. - Déborah Sulem; Michele Donini; Muhammad Bilal Zafar; Francois-Xavier Aubet; Jan Gasthaus; Tim Januschowski; Sanjiv Das; Krishnaram Kenthapadi; Cédric Archambeau (CoRR, 2022)

An Empirical Study of Simplicial Representation Learning with Wasserstein Distance. - Makoto Yamada; Yuki Takezawa; Guillaume Houry; Kira Michaela Dusterwald; Déborah Sulem; Han Zhao 002; Yao-Hung Hubert Tsai (CoRR, 2023)

Estimating the history of a random recursive tree. - Simon Briend; Christophe Giraud 002; Gábor Lugosi; Déborah Sulem (CoRR, 2024)

Graph similarity learning for change-point detection in dynamic networks. - Déborah Sulem; Henry Kenlay; Mihai Cucuringu; Xiaowen Dong 001 (Mach. Learn., 2024)