Dongdong Chen

DeepInverse has joined the PyTorch Ecosystem, making imaging with deep learning easier and more reproducible across research and industry. DeepInverse is an open source framework for solving imaging inverse problems in medical imaging, computational photography, remote sensing, astronomical imaging, microscopy and more. DeepInverse makes imaging with deep learning easy and is developed by a passionate community of researchers, practitioners and engineers. 🔗 Learn more & explore how to get involved: hubs.la/Q03RKyHJ0 #PyTorch #OpenSourceAI #DeepInverse #Imaging #DeepLearning

@ukmlv Congrats!

@ukmlv @IEEEsps Congrats! 🎉

🎉 Honored to receive the 𝗜𝗘𝗘𝗘 𝗦𝗣𝗦 𝗣𝗶𝗲𝗿𝗿𝗲-𝗦𝗶𝗺𝗼𝗻 𝗟𝗮𝗽𝗹𝗮𝗰𝗲 𝗘𝗮𝗿𝗹𝘆 𝗖𝗮𝗿𝗲𝗲𝗿 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁 𝗔𝘄𝗮𝗿𝗱 for contributions to computational imaging theory & practice. Grateful to the @IEEEsps community for this recognition!

Not coming back from Marseille empty handed #DeepInverse @TachellaJulian @MatthieuTerris @ddongchen @minhhai712

Toutes nos félicitations aux deux espoirs des prix science ouverte du logiciel libre de la recherche qui travaillent dans des laboratoires rattachés à @CNRSphysique : @TachellaJulian (DeepInverse) et Sébastien Weber (PyMoDAQ) 👏 Pour en savoir plus ⤵️ inp.cnrs.fr/fr/cnrsinfo/de…

🚀 deepinverse hackathon🚀 We just finished a couple of days working on deepinverse in the beautiful CIRM venue. deepinv.github.io/deepinv/ Immensely grateful to the dream team of contributors that participated in the hackathon! A thread 🧵

📢New preprint 📢 UNSURE: Unknown Noise level Stein's Unbiased Risk Estimator arxiv.org/abs/2409.01985… Optimal self-supervised losses (SURE, R2R) require exact knowledge of the noise distribution, and alternatives like Noise2Void are suboptimal. There is middle ground🧵

Tomorrow we are giving a deepinverse + computational imaging tutorial in Bologna, Italy, with fellow deepinverters @HuraultSamuel @MatthieuTerris @ddongchen site.unibo.it/mathematical-m…

Attending EUSIPCO'24 in Lyon? You can attend a 3-hour tutorial on self-supervised learning for imaging, given by Mike Davies and myself. eusipcolyon.sciencesconf.org/resource/page/… A thread with some of the contents 🧵

"pip install deepinv" to solve your inverse problems🥳🥳

@HuraultSamuel Congratulations 🎉🎉

Very honored to have received the PhD prize « Signal, Image, Vision » from the French research organizations EEA, GdR IASIS and GRETSI. Thanks a lot for this distinction.

🤗You can now check out some deepinverse denoisers with this interactive huggingface demo huggingface.co/spaces/deepinv… More demos are coming!

💣The deepinverse library keeps growing! Now you can train your model with the self-supervised loss 'recorrupted2recorrupted' by choosing the R2RLoss

People DeepIng into DeepInv at the DIPopt workshop 🤗

The group photo for DIPOpt at ENS Lyon, thanks everyone for coming and sharing ideas and research!

Update: Diffusion Posterior Sampling (DPS) is now integrated with deep inverse library (deepinv.github.io). Thanks @hyungjin_chung for the contribution! 'import deepinv as dinv' - one line of code to play with DPS.

🚆On my way to #ICCV2023 Tomorrow I'll be giving an intro to the deepinverse library in the morning deepinv.github.io/deepinv/

📢Happy to announce the "Deep learning, image analysis, inverse problems, and optimization" workshop on November 27-30 in Lyon, France. perso.ens-lyon.fr/nelly.pustelni… more details below 🧵

Do you need a library for inverse problems, computational imaging, or image reconstruction/restoration? try 'pip install deepinv', then 'import deepinv' is all you need! 🥳 deepinv.github.io #deepinverse

📢📢 Release of DeepInverse library 📢📢 After months of intense work, we are releasing the first stable version of DeepInverse deepinv.github.io/deepinv/, a PyTorch library for solving inverse problems with deep learning. with @HuraultSamuel, @MatthieuTerris and @ddongchen A 🧵