activity
20162026
most citedEpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models

27 citations · 45 across the 14 of their papers we have counts for

collaborators

14 papers

stat.ME2026

Meta-Analysis of High-Dimensional Surrogate Markers

Arthur Hughes, Rodolphe Thiébaut, Layla Parast +1

When direct measurement of a clinically relevant primary endpoint in a clinical trial is infeasible, a surrogate endpoint may be used instead to infer treatment effects. Trial-leve…

cs.DL2026★ 1 cited

Overcoming Barriers to Computational Reproducibility

Roman Hornung, László Németh, Oleksandr Zadorozhny +13

Computational reproducibility, the possibility for independent researchers to exactly reproduce published empirical results, is fundamental to science. Despite its importance, the…

stat.ME2026

Scalable Dirichlet Process Mixture Models with Unknown Concentration and Adaptive Covariance for High-Dimensional Clustering Applied to Leukemia Transcriptomics

Annesh Pal, Aguirre Mimoun, Rodolphe Thiébaut +1

We propose a novel method that performs adaptive clustering with DPMM using collapsed VI, while incorporating weakly-informative priors for DP concentration parameter alpha and bas…

cs.AI2025

Representation learning to advance multi-institutional studies with electronic health record data from US and France

Doudou Zhou, Han Tong, Linshanshan Wang +21

The widespread adoption of electronic health records has created new opportunities for translational clinical research, yet this promise remains constrained by fragmented data acro…

stat.ME2025

RISE: Two-Stage Rank-Based Identification of High-Dimensional Surrogate Markers Applied to Vaccinology

Arthur Hughes, Layla Parast, Rodolphe Thiébaut +1

In vaccine trials with long-term participant follow-up, it is of great importance to identify surrogate markers that accurately infer long-term immune responses. These markers offe…

stat.ME2024

Practical limitations for real-life application of data fission and data thinning in post-clustering differential analysis

Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut +1

Post-clustering inference in single-cell RNA sequencing (scRNA-seq) analysis presents significant challenges in controlling Type I error during differential expression analysis. Da…

stat.ME2022★ 2 cited

Post-clustering difference testing: valid inference and practical considerations

Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut +1

Clustering is part of unsupervised analysis methods that consist in grouping samples into homogeneous and separate subgroups of observations also called clusters. To interpret the…

stat.ML2022

On the potential benefits of entropic regularization for smoothing Wasserstein estimators

Jérémie Bigot, Paul Freulon, Boris P. Hejblum +1

This paper is focused on the study of entropic regularization in optimal transport as a smoothing method for Wasserstein estimators, through the prism of the classical tradeoff bet…

stat.ME2020★ 4 cited

Doubly-robust evaluation of high-dimensional surrogate markers

Denis Agniel, Layla Parast, Boris Hejblum

When evaluating the effectiveness of a treatment, policy, or intervention, the desired measure of effectiveness may be expensive to collect, not routinely available, or may take a…

cs.LG2020★ 27 cited

EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models

Cédric Colas, Boris Hejblum, Sébastien Rouillon +4

Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down,…

stat.CO2020★ 1 cited

Robust and Efficient Optimization Using a Marquardt-Levenberg Algorithm with R Package marqLevAlg

Viviane Philipps, Boris P Hejblum, Mélanie Prague +2

Implementations in R of classical general-purpose algorithms for local optimization generally have two major limitations which cause difficulties in applications to complex problem…

stat.AP2020★ 1 cited

CytOpT: Optimal Transport with Domain Adaptation for Interpreting Flow Cytometry data

Paul Freulon, Jérémie Bigot, Boris P. Hejblum

The automated analysis of flow cytometry measurements is an active research field. We introduce a new algorithm, referred to as CytOpT, using regularized optimal transport to direc…

stat.ML2017★ 6 cited

Sequential Dirichlet Process Mixtures of Multivariate Skew t-distributions for Model-based Clustering of Flow Cytometry Data

Boris P. Hejblum, Chariff Alkhassim, Raphael Gottardo +2

Flow cytometry is a high-throughput technology used to quantify multiple surface and intracellular markers at the level of a single cell. This enables to identify cell sub-types, a…

math.SG2016★ 3 cited

A completely integrable system on coadjoint orbits

Jeremy Lane

We construct a Gelfand-Zeitlin system on a one-parameter family of coadjoint orbits that are multiplicity-free Hamiltonian -spaces. Using this system we prove a lower…