Postdoc @ USC
AI for science and health | computer vision | diffusion models
https://z-fabian.github.io
Principal research scientist at Google DeepMind. Synthesized views are my own.
📍SF Bay Area 🔗 http://jonbarron.info
This feed is a mostly-incomplete mirror of https://x.com/jon_barron, I recommend you just follow me there.
Interpretable Deep Networks. http://baulab.info/ @davidbau
@Penn Prof, deep learning, brains, #causality, rigor, http://neuromatch.io, Transdisciplinary optimist, Dad, Loves outdoors, 🦖 , c4r.io
Research Scientist, Adobe
www.dogadogan.com
Intern @Google, Ph.D. Student @Cornell_CS.
Interested in machine learning, LLM, brain, and healthcare.
abehrouz.github.io
Foundations of AI. I like simple and minimal examples and creative ideas. I also like thinking about the next token 🧮🧸
Google Research | PhD, CMU |
https://arxiv.org/abs/2504.15266 | https://arxiv.org/abs/2403.06963
vaishnavh.github.io
Researcher in machine learning
Research Scientist @ Google DeepMind. Physics of learning, ML / AI, condensed matter. Prev Ph.D. Physics @ UC Berkeley.
Assistant Prof at Penn CIS | Postdoc at Microsoft Research | PhD from UT Austin CS | Co-founder LeT-All
ML Research @ Apple.
Understanding deep learning (generalization, calibration, diffusion, etc).
preetum.nakkiran.org
Director, Princeton Language and Intelligence. Professor of CS.
Cofounder & CTO @ Abridge, Raj Reddy Associate Prof of ML @ CMU, occasional writer, relapsing 🎷, creator of d2l.ai & approximatelycorrect.com
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst.
Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org
I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.
Physics-AI fellow at the University of Cambridge using physics to understand AI. Prev: EPFL, Amazon AWS AI.
https://alesfav.github.io/
Professor, University Of Copenhagen 🇩🇰 PI @belongielab.org 🕵️♂️ Director @aicentre.dk 🤖 Board member @ellis.eu 🇪🇺 Formerly: Cornell, Google, UCSD
#ComputerVision #MachineLearning
Professor at University of Toronto. Research on machine learning, optimization, and statistics.
theory of neural networks for natural and artificial intelligence
https://pehlevan.seas.harvard.edu/
