Publications

(You may also look at my Google Scholar and dblp profiles). I'm also currently updating my Github where you can find some of the code for the following articles and the resources for my courses.

■ Book/Theses   ■ Journal articles   ■ Conference papers   ■ Informal publications

Preprint / Under Review

  • M. Perez, R. Romero, B. Kang, T. De Bie, J. Lijffijt., C. Laclau. SimHawNet: a Modified Hawkes Process for Temporal Network Simulation.. Available on [arxiv].
  • C. Laclau, C. Largeron and M. Choudhary. A Survey on Fairness for Machine Learning on Graphs. Available on [arxiv].

Latest Publications

  • Q. Bouniot, I. Redko, AN. Mallasto, C. Laclau, ..., S. Kaski. From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport. paper. To appear @CVPR 2025.
  • T. Leteno, I. Proskurina et al. HistoiresMorales: A French Dataset for Assessing Moral Alignment. To appear @NAACL 2025.
  • F. Torba, C. Gravier, C. Laclau, A. Kammoun, J. Subercaze. Decoding the Hierarchy: A Hybrid Approach to Hierarchical Multi-Label Text Classification. ECIR 2025.
  • P. Krzakala, J. Yang, R. Flamary, F. d'Alché-Buc, C. Laclau, M. Labeau. Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss. NeurIPS 2024.
    [paper][code]
  • V. Brault, E. Devijver and C. Laclau. Mixture of segmentation for heterogeneous functional data. Electronic Journal of Statistics, 2024.
    [paper][code]
  • R. Serrano, C. Laclau, B. Jeudy, C. Largeron. Reconstructing the Unseen: GRIOT for Attributed Graph Imputation with Optimal Transport. ECML-PKDD, 2024.
  • F. Torba, C. Gravier, C. Laclau, A. Kammoun, J. Subercaze. A Study on Hierarchical Text Classification as a Seq2seq Task. ECIR, 2024.
  • A. Gourru, C. Laclau, M. Choudhary, and C. Largeron. Variational Perspective on Fair Edge Prediction. IDA, 2024
  • T. Leteno, A. Gourru, C. Laclau, C. Gravier Fair Text Classification with Wasserstein Independence. EMNLP, 2023.
  • J. Tissier, C. Laclau. Understanding the Benefits of Forgetting when Learning on Dynamic Graphs. ECML-PKDD, 2022.

Other

Student Supervision


PhD Students

  • 2024 ... - Lilian Marey: Revisiting Fairness on Graphs.
    Co-supervised with T. Viard and Deezer Research.
  • 2023 ... - Paul Krzakala: Optimal transport distance for modeling graph dynamics.
    Co-supervised with F. d'Alche-Buc and Remi Flamary.
  • 2023 ... - Mathilde Perez: Fairness in Temporal Graphs.
    Co-supervised with F. d'Alche-Buc.
  • 2022 ... - Richard Serrano: Machine Learning on Imperfect Graphs.
    Co-supervised with C. Largeron and B. Jeudy.
  • 2022 ... - Thibaud Leteno: Bias and fairness in compressed language models.
    Co-supervised with Christophe Gravier and Antoine Gourru - ANR Diké
  • 2021 ... - Fatos Torba: Hierarchical multi-label document classification in the context of tender responses to complex tenders.
    Co-supervised with Christophe Gravier, CIFRE with AITenders

Former Student

  • PhD (2015/2018) - Sumit Sidana : Recommender Systems for Online Advertising (co-supervised with M.-R. Amini)