☀️ Just wrapped up the DeepInverse Hackathon! We had 30+ imaging scientists from all over the world coding during 3 days next to the beautiful Calanques in Marseille, France. It was a great moment to meet new people, discuss science, and code new imaging algorithms!

🔬 Are you working in computational imaging or interested in learning? 📖 DeepInverse just released a new 5-minute quickstart tutorial deepinv.github.io/deepinv/auto... which gets you started developing AI models for reconstructing images!

New Feature in DeepInverse (deepinv.github.io): 🚀 Custom Diffusion Solver Design DeepInverse now simplifies the process with: ✔ Standard SDEs (VP, VE, etc.) ✔ Pretrained denoisers for multiple noise levels ✔ ODE/SDE solvers (Euler, Heun) ✔ Noisy data fidelity terms for guidance

I'll be in Singapore this week for #ICLR2025 presenting "UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate" Ping me if you are around too!

🚀🚀 Reconstruct-Anything-Model: A single model to rule all imaging tasks! We challenge current beliefs and show that a single U-Net can obtain impressive performance across a wide variety of tasks, **without** relying on expensive iterative schemes such as unrolling, PnP, diffusion

🚢🚢 deepinv v0.3.0 is here, with many new features! 🚢 🚢 Our passionate team of contributors keeps shipping more exciting tools! Deepinverse (deepinv.github.io) is a library for solving imaging inverse problems with deep learning.

Deriving Tweedie's formula from SURE let's you also derive other interesting generalisations, such as a formula that doesn't require knowledge about the noise level, and it can be generalized well beyond isotropic gaussian noise.

🚀 Do you want to learn about self-supervised learning for inverse problems? ▶️ Check out the 3-hour tutorial presented by Mike Davies (University of Edinburgh) and myself (CNRS, ENS Lyon), covering all the recent advances in a unified and simplified framework! youtube.com/playlist?lis...

Generalized Recorrupted-to-Recorrupted is accepted at CVPR25 🚀 See a thread below:

🚀 "UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate" is accepted at #ICLR2025 A thread! 📜 Paper: arxiv.org/abs/2409.01985 🖥️ Code: github.com/tachella/uns...

Deepinv v0.2.2 is out! documentation: deepinv.github.io repo: github.com/deepinv/deep... v0.2.2 updates: 📚 New documentation 📊 Metrics classes 🧠 Advanced MRI: 3D and multicoil support 🔥 Bregman potentials 🌀 Advanced transforms: diffeomorphisms, time transforms 🖼️ New datasets ⚡ L12 prior

🔉New paper "Generalized Recorrupted-to-Recorrupted" 🔉 with @bemc22.bsky.social and Jorge Bacca - Generalizes R2R self-supervised loss for noise belonging to the exponential family. - Shows asymptotic equivalence with SURE. paper: arxiv.org/abs/2412.04648 code: github.com/bemc22/Gener...

Yesterday I was very lucky to present in this beautiful seminar room at la universidad de la república 🇺🇾

🎉The open source library deepinverse has been awarded the best documentation prize of the open source code awards in France! www.inp.cnrs.fr/fr/cnrsinfo/...

Hi -- I have a postdoc position open in Computational MRI -- looking for experience and interest in MRI acquisition (in addition to reconstruction). Offer competitive pay. Opportunity to collaborate with Center for GenAI and Dell Med School. Bonus if you get your app in before Dec 1!

Para los hispanoparlantes, pueden encontrar una charla en el IAR sobre mi investigación en métodos de aprendizaje no supervisado aquí: www.youtube.com/live/-y-QCO9...

Let me know if you want me to add you to the list :)

I've made a starter pack of people I found here working on imaging inverse problems and computational imaging! go.bsky.app/QNkDcXE

Hello world