Anirban Ray

Super excited to present our poster (rayanirban.github.io/files/EMBL_p...) on HazeMatching and ResMatching at the EMBL AI and Biology Symposium 2026 in Heidelberg, Germany, this week. 🎉
If you’re around, please drop by our poster (#148 on Thursday, 12/3)! 😊

@embl.org #EESAIBio #AI4Science

Thank you so much @harschnitz.bsky.social 🙏😊

Update: ResMatching has been selected for an Oral Presentation at IEEE ISBI 2026! #ISBI2026! 🚀 😱 🎉

Being chosen for the oral track is a fantastic validation of the potential impact of this research. Thanks to the reviewers and organizers.

#cvpr2026 #cvpr2026 #microscopy #imagerestoration #generativeai #ai4science | Anirban Ray 🎉Excited to share that HazeMatching (https://lnkd.in/dP5kWAHS) has been accepted to IEEE/CVF #CVPR2026 (Findings)🎉. 🔬What if widefield microscopes produced confocal-quality images? We introduce Haze...

HazeMatching has been accepted to #CVPR2026 (Findings)! @cvprconference.bsky.social 🎉🎉

What if widefield microscopes could produce confocal-quality images? We introduce a Guided Conditional Flow Matching (CFM) framework that does exactly that.

Learn more here: www.linkedin.com/feed/update/...

We opened 4 PhD positions at @humantechnopole.bsky.social together with Polimi (see 👇).

My lab offers a PhD project on "Computational Morphogenesis": use state-of-the-art machine learning methods together with realistic simulations to build digital twins of developing tissue.

Apply by March 26.

Exciting news! An article on India BioImaging (IBI) has been published in "Microscopy and Analysis" (@wileylifesci.bsky.social )(Issue 2/2026)

Featured under "Building the India Bioimaging Community," it highlights IBI's vision, activities & growing impact in strengthening bioimaging across India.

Congratulations 🎊🍾🎉

Excited to share our new paper (CVPR 2026 🚀): "MuViT: Multi-Resolution Vision Transformers for Learning Across Scales in Microscopy" which enables local predictions to use global context.
Great work led by @albertdm.bsky.social & another fun collab w @gioelelamanno.bsky.social! @scadsai.bsky.social

It was super cool to hear @alex-krull.bsky.social talking about his research at @humantechnopole.bsky.social. Alex never fails to inspire his audience 🫠🤩

yeah exactly! I think that the training objective (minimizing drift between p and q) will inherently try to prioritize perception more than distortion (low FID), and with one-shot prediction, I feel that the chance of hallucination looks high (similar to GANs), but let's see!

haha, true! Aside from these, I find the idea of training time distribution evolution intriguing. Still trying to understand the implication of drifting models for inverse problems tho :)

Excellent talk by Matteo Hessel from Google DeepMind at @humantechnopole.bsky.social earlier today!
Thanks for dropping by and infecting us with the Meta-RL bug!

🤩

#isbi2026 #generativeai #flowmatching #computationalsuperresolution #bioimageanalysis | Anirban Ray Excited to share that ResMatching (https://lnkd.in/dn_6VB9Q) has been accepted to IEEE International Symposium on Biomedical Imaging (ISBI) 2026! 🎉🎉 This work represents a significant step forward in...

ResMatching accepted to IEEE ISBI 2025🎉. We extend Guided CFM to Computational Super-Resolution under extreme noise, achieving SOTA performance and calibrated posterior sampling that reflects uncertainty in real data. Learn more here: www.linkedin.com/posts/anirba...

How Residual Connections Are Getting an Upgrade [mHC] YouTube video by Jia-Bin Huang

Residual connections are adopted in virtually every deep learning model.

BUT, can we further improve it? Hyper-connections is an exciting recent exploration to generalize residual connections.

Check out the video explaining manifold constraints hyper-connections!
youtu.be/jYn_1PpRzxI

Self-Supervised Learning from Noisy and Incomplete Data Many important problems in science and engineering involve inferring a signal from noisy and/or incomplete observations, where the observation process is known. Historically, this problem has been tac...

📖 We put together with Mike Davies a review of self-supervised learning for inverse problems, covering the main approaches in the literature with a unified notation and analysis.

arxiv.org/abs/2601.03244

Image of the Human Technopole https://it.wikipedia.org/wiki/Human_Technopole#/media/File:Human_Technopole_Milano.jpg

I'm super excited to announce that I will join the Human Technopole @humantechnopole.bsky.social in Milan in April 2026 as a Research Group Leader.

Deep Learning for Microscopy Image Analysis Topics The following will be covered extensively during lectures, exercises, and project work: Image denoising and restoration (fully supervised and self-supervised) Image translation (e.g.,

🚨 Alarm!!! 🚨
AI/ML course for microscopy image analysis!!! 🧐
In 2026 at Janelia (@hhmijanelia.bsky.social), no tuition, housing and meals provided! Isn’t that borderline unbelievable?!?

20 students, ~14 TAs and lecturers
🗓️ June 4-18 2026

✍️ Jan 15 2026 ✍️

🔁 pls!!

www.janelia.org/you-janelia/...

Welcome to @humantechnopole.bsky.social, Jan 🤩

Okay, maybe I didn't pay much attention to this before but there are some elegant works that truly amaze me. This is one of them. A task-agnostic setup built on flow matching that just works across problems. I really like this work. 😀😃

Invited talk by Rich Sutton at @neuripsconf.bsky.social was presenting the OaK architecture.
A “scaffold” for superintelligent agents in which human inputs (at design time) are depreciated. 🧵

"Back to Basics: Let Denoising Generative Models Denoise" by
Tianhong Li & Kaiming He arxiv.org/abs/2511.13720
Diffusion models in pixel-space, without VAE, with clean image prediction = nice generation results. Not a new framework but a nice exploration of the design space of the diffusion models.

We moved the AI@MBL course "Deep Learning for Microscopy Image Analysis" to HHMI Janelia (@hhmijanelia.bsky.social).

Join us for two weeks of intense lectures, exercise, and hands-on project work!

Course dates: June 4-18 2026
Application by: January 15 2026

www.janelia.org/you-janelia/...

Congratulations 🎉🎊

💥 DeepInverse is now part of the official PyTorch Landscape💥

We are excited to join an ecosystem of great open-source AI libraries, including @hf.co diffusers, MONAI, einops, etc.

pytorch.org/blog/deepinv...

I’m at #AIS25 today and tomorrow…
Where scientists, industry leaders, investors, and policymakers meet to explore the transformative impact of artificial intelligence on scientific discovery.
I think this is a very important conversation we must have NOW! 👍

Anirban Ray, Vera Galinova, Florian Jug
ResMatching: Noise-Resilient Computational Super-Resolution via Guided Conditional Flow Matching
https://arxiv.org/abs/2510.26601

needless to say! and much appreciated 😊

super cool work😎

“We may not win every battle, but we will win the war.” --- Such an appropriate characterization for posterior samplers. Each posterior sample fights its own battle against noise and degradation; some win, some lose. But the MMSE estimate wins the war 😉.
#iykuk #ImageRestoration