A Scalable Biclustering Method for Heterogeneous Medical Data. - Maxence Vandromme; Julie Jacques; Julien Taillard; Laetitia Jourdan; Clarisse Dhaenens (MOD, 2016)

Extraction and optimization of classification rules for temporal sequences: Application to hospital data. - Maxence Vandromme; Julie Jacques; Julien Taillard; Arnaud Hansske; Laetitia Vermeulen-Jourdan; Clarisse Dhaenens (Knowl. Based Syst., 2017)

Automated Phenotyping of Patients with Non-Alcoholic Fatty Liver Disease Reveals Clinically RelevantDisease Subtypes. - Maxence Vandromme; Tomi Jun; Ponni Perumalswami; Joel T. Dudley; Andrea Branch; Li Li 062 (PSB, 2020)

Sequences of Sparse Matrix-Vector Multiplication on Fugaku's A64FX processors. - Jérôme Gurhem; Maxence Vandromme; Miwako Tsuji; Serge G. Petiton; Mitsuhisa Sato (CLUSTER, 2021)

Scaling the PageRank Algorithm for Very Large Graphs on the Fugaku Supercomputer. - Maxence Vandromme; Jérôme Gurhem; Miwako Tsuji; Serge G. Petiton; Mitsuhisa Sato (ICCS (1), 2022)

Efficient Parallel PageRank Algorithm for Network Analysis. - Maxence Vandromme; Serge G. Petiton (IPDPS Workshops, 2022)

A Biclustering Method for Heterogeneous and Temporal Medical Data. - Maxence Vandromme; Julie Jacques; Julien Taillard; Laetitia Jourdan; Clarisse Dhaenens (IEEE Trans. Knowl. Data Eng., 2022)

Graph structure and homophily for label propagation in Graph Neural Networks. - Maxence Vandromme; Serge G. Petiton (MCSoC, 2023)

Sequences of Distributed Matrix-Vector Product for Very Large and Very Sparse Irregular Matrices. - Maxence Vandromme; Nicolas Hochart; Serge G. Petiton; Jérôme Gurhem; Miwako Tsuji; Mitsuhisa Sato (SC Workshops, 2024)