Julian Tachella

CNRS & ENS de Lyon



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.


Apr 01, 2024 Our work on equivariant pnp algorithms is accepted at CVPR’24.
Jan 21, 2024 The equivariant bootstrap is accepted at AISTATS’24 with oral presentation.
Oct 23, 2023 Our paper on binary learning has been accepted in TMLR with a Featured certification!
Jul 06, 2023 The UNLIP project will be funded by the ANR. Job openings are coming soon!

selected publications

  1. tachella2023equivariant.png
    Equivariant Bootstrapping for Uncertainty Quantification in Imaging Inverse Problems
    Julian Tachella, and Marcelo Pereyra
    AISTATS 2024, Oral Presentation, 2024
  2. imagingequiv.png
    Imaging with Equivariant Deep Learning
    Dongdong Chen , Mike Davies , Matthias J Ehrhardt , Carola-Bibiane Schönlieb , Ferdia Sherry , and Julian Tachella
    IEEE Signal Processing Magazine, 2023
  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