🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

I had a lot of fun helping put this problem set together -- if you're teaching diffusion models + computer vision, consider using this homework for your course! (links at end of Ryan Tabrizi's thread!)

An Empirical Study of Autoregressive Pre-training from Videos. paper: arxiv.org/pdf/2501.05453 website: brjathu.github.io/toto We empirically study autoregressive pre-training from videos. Our models are pre-trained on a diverse dataset of videos and images comprising over 1

Decentralized Diffusion Models power stronger models trained on more accessible infrastructure. DDMs mitigate the networking bottleneck that locks training into expensive and power-hungry centralized clusters. They scale gracefully to billions of parameters and generate

Happy to announce that our paper on “Scaling Properties of Diffusion Models For Perceptual Tasks" has been accepted to CVPR 2025! 🥳 🎉 We present a detailed study on how to efficiently scale conditional diffusion models for perceptual tasks under a unified framework. Our

Introducing Carl, the first AI system to create a research paper that passes peer review. Carl's work was just accepted at an @ICLR_conf workshop on the Tiny Papers track. Carl forms new research hypotheses, tests them & writes up results. Learn more: autoscience.ai/blog/meet-carl…

Do LLMs understand probability distributions? Can they serve as effective simulators of probability? No! However, in our latest paper that via in-context learning, LLMs update their broken priors in a manner akin to Bayseian updating. 📝 arxiv.org/abs/2503.04722

Excited to announce our new preprint, "Training Video Foundation Models with NVIDIA NeMo." Paper: arxiv.org/abs/2503.12964

Very excited to share Stable Virtual Camera, a generalist diffusion model for view synthesis: stable-virtual-camera.github.io It scales well with data, and works out-the-box for different NVS tasks. Code and 🤗 demo are released! 🧵(1/N)

our new system trains humanoid robots using data from cell phone videos, enabling skills such as climbing stairs and sitting on chairs in a single policy (w/ Hongsuk Benjamin Choi Junyi Zhang David McAllister)

Excited to introduce PyRoki ("Python Robot Kinematics"): easier IK, trajectory optimization, motion retargeting... with an open-source toolkit on both CPU and GPU

I had a pleasure TA’ing this class! Check out the material, especially the flow matching from scratch assignment!

woohoo! so excited to finally share this. check out the website, and sound ON!! It's craaaazy how much of a difference it makes to hear your videos. 🔊

I'm excited to share that I’ll be joining Univ. of Maryland as an Assistant Professor in Computer Science, where I’ll be launching the Resilient AI and Grounded Sensing Lab. The RAGS Lab will build AI that works in chaotic environments. If you would like to partner, please DM me!

coming to the Exploratorium today! thank you Dr. Catie Cuan for bringing me along on this wild adventure :) exploratorium.edu/visit/calendar…