
Sam Charrington
· 41 Minutes
Probabilistic Numeric CNNs with Roberto Bondesan - #482
Listen
Today we kick off our ICLR 2021 coverage joined by Roberto Bondesan, an AI Researcher at Qualcomm.
In our conversation with Roberto, we explore his paper Probabilistic Numeric Convolutional Neural Networks, which represents features as Gaussian processes, providing a probabilistic description of discretization error. We discuss some of the other work the team at Qualcomm presented at the conference, including a paper called Adaptive Neural Compression, as well as work on Guage Equvariant Mesh CNNs. Finally, we briefly discuss quantum deep learning, and what excites Roberto and his team about the future of their research in combinatorial optimization.
The complete show notes for this episode can be found at https://twimlai.com/go/482
Original source
This story was published by The TWIML AI Podcast and written by Sam Charrington. SyncAI.news shows a preview; the complete article is on the publisher's site.
Read the full story on twimlai.com
![[AINews] Here are 6 Clones of Jev in 2 days](/media/images/2026/09/6388df7f93fa6767.webp)
![[AINews] not much happened today](/media/images/2026/09/e8357327b4721fb2.webp)
