It was a dream come true to teach the course I wish existed at the start of my PhD. We built up the algorithmic foundations of modern-day RL, imitation learning, and RLHF, going deeper than the usual "grab bag of tricks". All 25 lectures + 150 pages of notes are now public!

I have a draft of my introduction to cooperative multi-agent reinforcement learning on arxiv. Check it out and let me know any feedback you have. The plan is to polish and extend the material into a more comprehensive text with Frans Oliehoek. arxiv.org/abs/2405.06161

The are lots of people who've influenced AI but haven't won Nobel prizes. I discuss a tiny sliver of them in this parody of @billyjoelofficial.bsky.social 's "We didn't start the fire"... Enjoy! youtube.com/shorts/qDSYA...

If you are into ML theory (RL or not) with a proven track record, and you are interested in an industry research position, PM me. Feel free to spread the word.

A common question nowadays: Which is better, diffusion or flow matching? 🤔 Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.

Anne Gagneux, Ségolène Martin, @quentinbertrand.bsky.social Remi Emonet and I wrote a tutorial blog post on flow matching: dl.heeere.com/conditional-... with lots of illustrations and intuition! We got this idea after their cool work on improving Plug and Play with FM: arxiv.org/abs/2410.02423

Intro Post Hello World! I'm a 2nd year Robotics PhD student at CMU, working on distributed dexterous manipulation, accessible soft robots and sensors, sample efficient robot learning, and causal inference. Here are my cute robots: PS: Videos are old and sped up. They move slower in real-world :3