Preprints

  • S Barthelme. An Introduction to Determinantal Point Processes and Related Topics. Book draft: see here
  • Barthelmé, S., Castell, F., Gaudillière, A., Mélot, C., Quattropani, M., & Tremblay, N. (2025). Spectrum Estimation through Kirchhoff Random Forests. arXiv:2507.19164.

2025

  • M Gjorgjevski, N Keriven, S Barthelmé, Y De Castro (2025). Node Regression on Latent Position Random Graphs via Local Averaging. To appear in Journal of Machine Learning Research. arXiv:2410.21987
  • H Jaquard, PO Amblard, S Barthelmé, N Tremblay. Random Multi-Type Spanning Forests for Synchronization on Sparse Graphs (2025). SIAM Journal on Mathematics of Data Science 7 (3), 1123-1153 arXiv:2403.19300
  • K Usevich, S Barthelme. Computing asymptotic eigenvectors and eigenvalues of perturbed symmetric matrices (2025). To appear in SIAM Linear Algebra arXiv:2407.17047
  • YL Fay, N Chopin, S Barthelmé (2025). Least squares variational inference. Neural Information Processing Systems*

2024

  • S Barthelmé, PO Amblard, N Tremblay, K Usevich (2024). Gaussian process regression in the flat limit. The Annals of Statistics 51 (6), 2471-2505

2023

  • H Jaquard, M Fanuel, PO Amblard, R Bardenet, S Barthelmé, N Tremblay. Smoothing complex-valued signals on Graphs with Monte-Carlo (2023). ICASSP. arxiv:2210.08014

  • S Barthelmé, N Tremblay, PO Amblard. A Faster Sampler for Discrete Determinantal Point Processes (2023). AISTATS. arXiv:2210.17358

  • Barthelmé, S., Tremblay, N., Usevich, K., & Amblard, P. O. (2022). Determinantal Point Processes in the Flat Limit: Extended L-ensembles, Partial-Projection DPPs and Universality Classes. Bernoulli. arXiv:2007.04117

  • N Tremblay, S Barthelmé, K Usevich, PO Amblard. Extended L-ensembles: a new representation for Determinantal Point Processes. The Annals of Applied Probability. arXiv:2107.06345

2022

  • YY Pilavcı, PO Amblard, S Barthelmé, N Tremblay. Variance Reduction in Stochastic Methods for Large-Scale Regularized Least-Squares Problems. EUSIPCO. arXiv:2110.07894

  • P Maho, C Herrier, T Livache, P Comon, S Barthelme. A calibrant-free drift compensation method for gas sensor arrays. Chemometrics and Intelligent Laboratory Systems. hal-03409223

2021

  • YY Pilavcı, PO Amblard, S Barthelmé, N Tremblay. Graph Tikhonov regularization and interpolation via random spanning forests. IEEE transactions on Signal and Information Processing over Networks. arXiv:2011.10450

  • Maho, P., Herrier, C., Livache, T., Comon, P., & Barthelme, S. (2020). Real-time gas recognition and gas unmixing in a robot application. Sensors & Actuators B. hal-02534216v2

2020

  • Barthelmé, S., & Usevich, K. (2020). Spectral properties of kernel matrices in the flat limit. arXiv:1910.14067. To appear in SIAM Journal on Matrix Analysis and Applications.

  • Maho, P., Herrier, C., Livache, T., Rolland, G., Comon, P., & Barthelmé, S. (2020). Reliable chiral recognition with an electronic nose. Biosensors and Bioelectronics, 112183. hal-02534216

  • Pilavci, Y. Y., Amblard, P. O., Barthelmé, S., & Tremblay, N. (2020). Smoothing graph signals via random spanning forests. arXiv:1910.07963. ICASSP.

2019

  • Breuil, C., Jennings, B. J., Barthelmé, S., & Guyader, N. (2019). Color improves edge classification in human vision. PLoS Computational Biology, 15(10).

  • Barthelmé, S, Tremblay, N, Gaudillière, A, Avena, L, Amblard, P O (2019). Estimating the Inverse Trace using Random Forests on Graphs. GRETSI. arXiv:1905.02086

  • Maho, P., Dolcinotti, C., Livache, T., Herrier, C., Andreev, A., Comon, P., & Barthelme, S. (2019). GRETSI. Reconnaissance de plusieurs composés chimiques à l’aide d’un robot équipé d’un nez électronique.

  • Trukenbrod, H. A., Barthelmé, S., Wichmann, F. A., & Engbert, R. (2019). Spatial statistics for gaze patterns in scene viewing: Effects of repeated viewing. Journal of Vision, 19(6), 5-5.

  • Barthelmé, S., Amblard, P. O., & Tremblay, N. (2019). Asymptotic Equivalence of Fixed-size and Varying-size Determinantal Point Processes. Bernoulli

  • Maho, P., Dolcinotti, C., Livache, T., Herrier, C., Andreev, A., Comon, P., & Barthelme, S. (2019). Olfactive robot for gas discrimination over several months using a new optoelectronic nose. ISOEN

2018

  • Pierre Maho, Simon Barthelme, Pierre Comon (2018). Non-linear source separation under the Langmuir model for chemical sensors. IEEE Sensor Array and Multichannel Signal Processing Workshop. [hal:01802358]

  • Tremblay, N., Barthelmé, S., & Amblard, P. O. (2018). Determinantal Point Processes for Coresets. arXiv:1803.08700. Now published in JMLR.

2017

  • Tremblay, N., Amblard, P. O., & Barthelmé, S. (2017) Graph sampling with determinantal processes. In Signal Processing Conference (EUSIPCO), 2017 25th European (pp. 1674-1678). IEEE. arXiv:1703.01594

  • Tremblay, N., Barthelme, S., & Amblard, P. O. (2017). Echantillonnage de signaux sur graphes via des processus déterminantaux. GRETSI. arXiv:1704.02239.

  • Dehaene, G, Barthelme, S (2017)  Expectation Propagation in the large-data limit. Journal of the Royal Statistical Society Series B. arXiv:1503.08060

2016

  • Grabska-Barwińska, A., Barthelmé, S., Beck, J., Mainen, Z. F., Pouget, A., & Latham, P. E. (2016). A probabilistic approach to demixing odors. Nature neuroscience, 20(1), 98-106.

  • Gruenhage, G., Opper M, Barthelme, S (2016). Visualizing the effects of a changing distance using continuous embeddings. Computational Statistics and Data Analysis arXiv:1311.1911

2015

  • Dehaene, G, Barthelme, S (2015). Bounding Errors of Expectation-Propagation. *Advances in Neural Information Processing Systems (NIPS). * arXiv:1601.02387

  • Barthelmé, S., Chopin, N., and Cottet, V. Divide and conquer in ABC: Expectation-Progagation algorithms for likelihood-free inference. Handbook of Approximate Bayesian Computation (S. Sisson, L. Fan, M. Beamont, eds.) arXiv:1512.00205

  • Barthelme, S, Chopin, N (2015) The Poisson Transform for Unnormalised Statistical Models. Statistics and Computing arXiv:1406.2839

2014

  • Engbert, R, Trukenbrod, H, Barthelme, S, Wichmann, F (2014). Spatial statistics and attentional dynamics in scene viewing*. Journal of Vision.* arXiv:1405.3270

  • Barthelme, S. (2014). Fast matrix computations for functional additive models. Statistics & Computing. arXiv:1402.4984

  • Barthelmé, S., & Chopin, N. (2014). Expectation propagation for likelihood-free inference. Journal of the American Statistical Association, 109(505), 315-333. arXiv:1107.5959

2013

  • Simon Barthelmé, Hans Trukenbrod, Ralf Engbert, Felix Wichmann. Modelling fixation locations using spatial point processes. In press at Journal of Vision. http://arxiv.org/abs/1207.2370

2011

  • Simon Barthelmé, Nicolas Chopin (2011). ABC-EP: Expectation Propagation for Likelihood-free Bayesian Computation, ICML 2011 (Proceedings of the 28th International Conference on Machine Learning), L. Getoor and T. Scheffer (eds), 289-296.

  •   Simon Barthelmé, Nicolas Chopin (2011). Discussions of `Riemann manifold Langevin and Hamiltonian Monte Carlo methods" by Girolami and Calderhead. *Journal of the Royal Statistical Society, Series B, *73(2), 173.

2010

  • Simon Barthelmé, Pascal Mamassian. (2010). Flexible mechanisms underlie the evaluation of visual confidence. Proceedings of the National Academy of Sciences, 107(48):20834-20839. PDF. Supplementary info.

2009

  • Simon Barthelmé, Pascal Mamassian (2009). Evaluation of Objective Uncertainty in the Visual System. PLoS Computational Biology. Available online here.

  • Patrick J. Mineault, Simon Barthelmé, Christopher C. Pack (2009).  Improved classification images with sparse priors in a smooth basis. Journal of Vision. Available online here.