Articles

Vacher J., Meso A., Perrinet L., Peyré G. (2018), Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures, Neural Computation, vol. 130, n°12, p. 3355-3392

Briand T., Vacher J. (2016), How to Apply a Filter Defined in the Frequency Domain by a Continuous Function, Image Processing On Line , vol. 6, p. 183-211

Briand T., Vacher J., Galerne B., Rabin J. (2014), The Heeger & Bergen Pyramid Based Texture Synthesis Algorithm, Image Processing On Line , vol. 4, p. 276 - 299

Communications avec actes

Vacher J., Muzellec B., Rudi A., Bach F., Vialard F-X. (2021), A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation, in Mikhail Belkin, Samory Kpotufe, COLT 2021 - 34th Annual Conference on Learning Theory, Journal of Machine Learning Research, 4143-4173 p.

Vacher J., Meso A., Perrinet L., Peyré G. (2015), Biologically Inspired Dynamic Textures for Probing Motion Perception, in , Advances in Neural Information Processing Systems 28 (NIPS 2015), Montreal, IEEE - Institute of Electrical and Electronics Engineers, 17 p.

Prépublications / Cahiers de recherche

Muzellec B., Vacher J., Bach F., Vialard F-X., Rudi A. (2021), Near-optimal estimation of smooth transport maps with kernel sums-of-squares, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 28 p.