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Congratulations to Durk Kingma and Max Welling for winning the inaugural ICLR Test of Time Award for their amazing work on Auto-Encoding Variational Bayes, the paper that proposed Variational Autoencoders! arxiv.org/abs/1312.6114

Thanks to the ICLR Award Committee! And thank you for the kind words, Max! You were the perfect Ph.D. advisor and collaborator, kind and inspiring. I really couldn't have wished for better.

📢 Excited to share EM Distillation (EMD), a maximum likelihood method that distills pretrained diffusion models to one-step generators. EMD gracefully interpolates between mode-seeking and mode-covering KL to better capture the teacher's distribution. arxiv.org/abs/2405.16852

#Master #AI at UvA Amsterdam closing the academic year with Durk Kingma

The recording of our talk for the ICLR'24 test-of-time award (with Max Welling) is now available online: iclr.cc/virtual/2024/t… Biggest live audience I've ever spoken to, with >2000 attendees 😅. But it was a lot of fun!

Congrats to Geoffrey Hinton for getting the Nobel! His impact is immeasurable, very much deserved.

In arxiv.org/abs/2303.00848, Durk Kingma and Ruiqi Gao had suggested that noise augmentation could be used to make other likelihood-based models optimise perceptually weighted losses, like diffusion models do. So cool to see this working well in practice!

Great blogpost by Ruiqi (and other GDM ex-colleagues), clearly explaining the the connection between flow matching and diffusion models. Super happy they took the time to explain this topic, there's confusion on this topic, I think many will find this quite valuable!

👇 Great work led by Yushun (Yushun Zhang) introducing Adam-mini, a version of Adam that, surprisingly, reduces Adam's memory requirement by 50% (!), without negatively affecting convergence rates. Please read Yushun's thread for details!

Thank you! See you guys in Singapore next week 🥳

Doing ICLR'25 test of time award with Jimmy Ba in a few mins