Launching Lean Co-pilot for LLM-human collaboration to write formal mathematical proofs that are 100% accurate. We use LLMs to suggest proof tactics in Lean and also allow humans to intervene and modify in a seamless manner. github.com/lean-dojo/Lean… Automating theorem proving

🏆 Our paper "Deep Multimodal Fusion for Surgical Feedback Classification" won the best proceedings paper at ML4H! 🎉 tinyurl.com/deep-surgical-… We're revolutionizing #SurgicalTraining by automating feedback analysis using #MachineLearning. We've developed the first #AI

Gianmarco Pinton talking about ultrasound imaging and also our collaboration using neural operators for the inverse problem of image reconstruction

I am looking to hire several Ph.D. students starting Fall 2025 JHU ECE. Anyone who is passionate for computational imaging/machine learning/statistical inference is welcome to apply. MS/Postdoc positions are also available! Here is the link: forms.gle/dFyftuPTSCqSTa… #PhDposition

Excited to present at NeurIPS 2024! 🎉 We propose a unified neural operator for Compressed Sensing MRI, adapting to multiple undersampling patterns/rates, with 11% SSIM & 4dB PSNR gains. Full paper & code: armeet.ca/nomri #NeurIPS2024 #ML #MRI #NeuralOperators

Excited to share that our paper, "Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness Assessment," won a Best Paper Award 🏆 at #ML4H2024! Join us on Monday (12/16) at ML4H for our spotlight talk at 1:50pm and poster session at 2:15pm. We propose a

Happening now. I am giving a talk at NeurIPS Conference AIM-FM workshop at 3:30 today. If you want to learn about foundation models other than LLMs come to East ballroom A/B.

Happy to share our first ML4H work on predicting the safety of IMRT plans. IMRT is an important cancer treatment, which needs to undergo measurement for quality assurance. However, it is very time consuming. Applying ML to help radiation physicists is safety-critical.

2024 was a pivotal year for AI+Science. Our team made exciting contributions. Here are some highlights: tensorlab.cms.caltech.edu/users/anima/20… 1. Neural Operators as a unifying AI framework for modeling multi-scale processes. We got to write a perspective article in Nature Reviews Physics and released an

Excited to share our work that detects 3D bounding boxes from 2D images. Plus, you can freely query detection boxes with any unbounded (open) vocabulary! Try our code: github.com/UVA-Computer-V…

Please consider making a contribution to this special fund that will be used by Caltech and JPL to directly support affected individuals and their families greatly impacted by this week's devastating fires in Southern California. giving.caltech.edu/areas-to-suppo…

I’m presenting our work at CVPR this week and happy to chat! 1) Thu 6/12 10am talk A 107A Practical/Theoretical Gap workshop 2) Thu 6/12 11:30am talk A 101D Embodied AI workshop 3) Sun 6/15 morning poster session: A Unified Model for Accelerated MRI

Check out our poster on neural operators for medical imaging today #CVPR2025

Try out the Hugging Face Spaces live demo! huggingface.co/spaces/armeet/…

Amazing time at #CVPR with brilliant minds! Big congrats to Prof. Anima Anandkumar on receiving the IEEE Award! 🏆 Your mentorship light my way Shout-out to Armeet for making any-resolution neural operators for imaging possible. Check out the demo: huggingface.co/spaces/armeet/…

Can scaling data and models alone solve computer vision? 🤔 Join us at the SP4V Workshop at #ICCV2025 in Hawaii to explore this question! 🎤 Speakers: Danfei Xu, joao carreira, Jiajun Wu, Kristen Grauman, Saining Xie, Vincent Sitzmann 🔗 sp4v.github.io