1. Vacher, J. & Coen-Cagli, R. Combining mixture models with linear mixing updates: multilayer image segmentation and synthesis. arXiv preprint arXiv:1905.10629 (2019).
  2. Vacher, J., Mamassian, P. & Coen-Cagli, R. Probabilistic Model of Visual Segmentation. arXiv preprint arXiv:1806.00111 (2019).


  1. Le Coënt, A., Fribourg, L., Vacher, J. & Wisniewski, R. Probabilistic reachability and control synthesis for stochastic switched systems using the tamed Euler method. Nonlinear Analysis: Hybrid Systems 36, 100860 (2020).
  2. Roggerone, V., Vacher, J., Tarlao, C. & Guastavino, C. Auditory motion perception emerges from successive sound localizations integrated over time. Scientific Reports 9, 16437 (2019).
  3. Vacher, J., Meso, A. I., Perrinet, L. U. & Peyré, G. Bayesian modeling of motion perception using dynamical stochastic textures. Neural computation 30, 3355–3392 (2018).
  4. Briand, T. & Vacher, J. How to Apply a Filter Defined in the Frequency Domain by a Continuous Function. Image Processing On Line 6, 2016–11 (2016).
  5. Briand, T., Vacher, J., Galerne, B. & Rabin, J. The Heeger-Bergen Pyramid-Based Texture Synthesis Algorithm. Image Processing On Line 4, 2014–11 (2014).


  1. Vacher, J., Davila, A., Kohn, A. & Coen-Cagli, R. Texture Interpolation for Probing Visual Perception. Advances in Neural Information Processing Systems (Spotlight – top 5%) (2020).
  2. Le Coënt, A., Fribourg, L. & Vacher, J. Control Synthesis for Stochastic Switched Systems using the Tamed Euler Method. in IFAC-PapersOnLine 51, 259–264 (2018).
  3. Vacher, J., Meso, A. I., Perrinet, L. U. & Peyré, G. Biologically inspired dynamic textures for probing motion perception. in Advances in Neural Information Processing Systems (Spotlight – top 5%) (2015).

PhD Manuscript

  1. Vacher, J. Dynamic Textures Synthesis for Probing Vision in Psychophysics and Electrophysiology. (Paris Dauphine University, 2017).

© 2019. All rights reserved.

Powered by Hydejack v8.4.0