Julian Tachella

CNRS & ENS de Lyon

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julian.tachella@cnrs.fr

I am a research scientist at the French National Centre for Scientific Research CNRS, working at the Sisyph laboratory, École Normale Supérieure de Lyon (Lyon, France). My research lies at the intersection of signal processing and machine learning. I am particularly interested in the theory of imaging inverse problems and applications in computational imaging.

I am a lead developer of the deep inverse, a library for solving inverse problems with deep learning.

Open PhD and master positions can be found here.

Code and videos related to my publications can be found here.

news

Mar 15, 2025 A 3-hour self-supervised tutorial is now available in YouTube! find videos and more here.
Feb 07, 2025 Unknown Noise Level Stein’s Unbiased Estimate is accepted at ICLR’25.
Sep 25, 2024 We have an open postdoc position, see details here.
Jul 01, 2024 We are presenting a 3-hour tutorial on self-supervised learning for imaging at EUSIPCO’24, find slides and more here.
Apr 01, 2024 Our work on equivariant pnp algorithms is accepted at CVPR’24.

selected publications

  1. terris2025ram.png
    Reconstruct Anything Model: a lightweight foundational model for computational imaging
    Matthieu Terris , Samuel Hurault , Maxime Song , and Julián Tachella
    2025
  2. UNSURE_demo.png
    UNSURE: self-supervised learning with Unknown Noise level and Stein’s Unbiased Risk Estimate
    Julian Tachella, Mike Davies , and Laurent Jacques
    ICLR 2025, 2025
  3. m_regimes_website.png
    Sensing Theorems for Unsupervised Learning in Linear Inverse Problems
    Julian Tachella, Dongdong Chen , and Mike Davies
    Journal of Machine Learning Research (JMLR), Jan 2023