Publications

Preprints

    Journals

    1. Vacher, J., Launay, C. & Coen-Cagli, R. Flexibly Regularized Mixture Models and Application to Image Segmentation. Neural Networks 149, 107–123 (2022).
    2. Vacher, J. & Briand, T. The Portilla-Simoncelli Texture Model: towards Understanding the Early Visual Cortex. Image Processing On Line 11, 170–211 (2021).
    3. 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).
    4. Roggerone, V., Vacher, J., Tarlao, C. & Guastavino, C. Auditory motion perception emerges from successive sound localizations integrated over time. Scientific Reports 9, 16437 (2019).
    5. 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).
    6. 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).
    7. Briand, T., Vacher, J., Galerne, B. & Rabin, J. The Heeger-Bergen Pyramid-Based Texture Synthesis Algorithm. Image Processing On Line 4, 2014–11 (2014).

    Conferences (Proceedings)

    1. Vacher, J., Davila, A., Kohn, A. & Coen-Cagli, R. Texture Interpolation for Probing Visual Perception. Advances in Neural Information Processing Systems (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 (2015).

    Conferences (No Proceedings)

    1. Vacher, J., Mamassian, P. & Coen-Cagli, R. Measuring Human Probabilistic Segmentation Maps. in Cosyne Abstracts (2020).

    PhD Manuscript

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

    Unpublished Reports

    1. Vacher, J., Mamassian, P. & Coen-Cagli, R. Probabilistic Model of Visual Segmentation. arXiv preprint arXiv:1806.00111 (2019).

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