Preprints

• H. D. Nguyen, J. Westerhout, T. Guilmeau, J. Arbel. Consistency of variational approximations under bounded Kullback-Leibler divergence. Submitted, 2026. arXiv

Journal papers

• T. Guilmeau, E. Chouzenoux, V. Elvira. Regularized Rényi divergence minimization through Bregman proximal gradient algorithms. Journal of Machine Learning Research, vol. 26(157), pp. 1-56, 2025. JMLR ⸱ arXiv
• T. Guilmeau, E. Chouzenoux, V. Elvira. A divergence-based condition to ensure quantile improvement in black-box global optimization. IEEE Transactions on Evolutionary Computation, vol. 29(4), pp. 1017-1028, 2025. DOI ⸱ arXiv
• P. Gajardo, T. Guilmeau, C. Hermosilla. Sensitivity analysis of the set of sustainable thresholds. Set-Valued and Variational Analysis, vol. 32(18), 2024. DOI ⸱ HAL
• T. Guilmeau, E. Chouzenoux, V. Elvira. On variational inference and maximum likelihood estimation with the λ-exponential family. Foundations of Data Science, vol. 6(1), pp. 85-123, 2024. DOI ⸱ arXiv
• T. Guilmeau, A. Rapaport. Multiplicity of neutrally stable periodic orbits with coexistence in the chemostat subject to periodic removal rate. SIAM Journal on Applied Mathematics, vol. 84(1), pp. 39-59, 2024. DOI ⸱ HAL
• T. Guilmeau, A. Rapaport. Singular arcs in optimal periodic control problems with scalar dynamics and integral input constraint. Journal of Optimization, Theory and Applications, vol. 195, pp. 953-975, 2022. DOI ⸱ HAL

Conference papers

• T. Guilmeau, H. Hendrikx, F. Forbes. Convergence of projected stochastic natural gradient variational inference for various step size and sample or batch size schedules. International Conference on Artificial Intelligence and Statistics (AISTATS), 2026. OpenReview ⸱ arXiv
• T. Guilmeau*, N. Branchini*, E. Chouzenoux, V. Elvira. Adaptive importance sampling for heavy-tailed distributions via α-divergence minimization. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024. PMLR ⸱ arXiv
  * equal contribution
• T. Guilmeau, E. Chouzenoux, V. Elvira. Adaptive simulated annealing through alternating Renyi divergence minimization. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. DOI ⸱ HAL
• T. Guilmeau, E. Chouzenoux, V. Elvira. Proximal-based adaptive simulated annealing for global optimization. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022. DOI ⸱ HAL
• F. Dupeuble, A. Rapaport, T. Guilmeau, J. Tchouanti, B. Enjalbert, C. Bideaux, J.-P. Steyer, A. Feddaoui-Papin, J. Harmand. Deterministic models to decipher the lag phase duration during diauxie. IFAC-PapersOnLine, vol. 55, issue 20, pp. 481-486, 2022. DOI ⸱ HAL
• T. Guilmeau, E. Chouzenoux, V. Elvira. Simulated annealing: a review and a new scheme. IEEE Statistical Signal Processing Workshop (SSP), 2021. DOI ⸱ HAL

Presentations

• Contributed talk at the International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC), 2026.
• Contributed talk during the Journées de Statistiques de la SfdS, 2026.
• Poster presentation at Statlearn 2026.
• Invited talk at the Applied Mathematics Seminar (Laboratoire de Mathématiques Jean Leary, Nantes Université, France), 2026.
• Invited talk at the DATA Seminar (Laboratoire Jean Kuntzmann, Université Grenoble Alpes, France), 2025.
• Invited talk at EUROPT 2025.
• Invited talk at EUROPT 2024.
• Contributed talk at the PGMODays 2023.
• Poster presentation at the International Conference on Monte Carlo Methods and Applications (MCM), 2023.
• Invited talk at the MOP Research Seminar (Mathematical Optimization for Data Science Group, Saarland University, Germany), 2023.
• Poster presentation at the ICST PhD day, 2023.
• Contributed talk at the PGMODays 2022.
• Contributed talk at the PGMODays 2021.
• Poster presentation at the CIRM Workshop On Future Synergies for Stochastic and Learning Algorithms, 2021.
• Talk at Journées Thématiques du LBE, 2020.