📣 #ICIP2026 invites proposals for Satellite Workshops on focused or emerging topics in image processing, vision and imaging, not specifically covered in the main conference.
📅 Submissions due 21 January 2026
🔗 Learn more: https://t.co/liaRBp9CZq
Michael Jordan gave a short, excellent, and provocative talk recently in Paris - here's a few key ideas
- It's all just machine learning (ML) - the AI moniker is hype
- The late Dave Rumelhart should've received a Nobel prize for his early ideas on making backprop work
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The tech industry in Silicon Valley runs on the considerable talents and work ethic of folks who were not born here. Many of these folks were also trained in this country in our Universities. This is our strength.
If we mess with this virtuous cycle, it is at our own peril.
Once-beloved topic: efficient signal, image, graph transformations like Discrete Cosine or Sine Transforms (DCT/DST), for data analysis, sparsity, compression. Antonio Ortega DCTs, DSTs and transforms on path graphs: History and recent results @elpenta
https://t.co/7DB4hXZj0y
As someone who has reported on AI for 7 years and covered China tech as well, I think the biggest lesson to be drawn from DeepSeek is the huge cracks it illustrates with the current dominant paradigm of AI development. A long thread. 1/
🚨 The 8th annual Graph Signal Processing Workshop is back this May 14-16! Held in Montreal, CA, at @Mila_Quebec, we’re covering all things graphs, signals, learning, & applications 🕸️〰️
🔗: https://t.co/s5olwuXvt7
👉🏻Abstract submission opens Feb 1
👉🏻 Registration opens Mar 20
The Delaunay triangulation is the dual of the Voronoi diagram. The most fundamental tool of computational geometry. https://t.co/GzE8Pi3Joz https://t.co/Y1zWHcn7Lr https://t.co/6T57pG5dOo
I'm pleased to share that our recent paper with @2ptmvd has been accepted to the Philoshophical Transactions of the Royal Society. Here's the ‘Accepted Author Version’:
https://t.co/dUibTgqRF7
And here it is on arxiv without the fancy formatting:
https://t.co/0Ocmqv5sqV
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Congratulations to @USCViterbi researchers Urbashi Mitra, Bistra Dilkina (@BDilkina), and Gisele Ragusa! They'll provide expertise on AI/machine learning, data analytics, and algorithm design for the new @NSF Center for Pandemic Insights. https://t.co/RjgPlaMvbz
Tutorial on Diffusion Models for Imaging and Vision
2nd edition is up on arXiv
https://t.co/fWv111nG5M
(51 pages --> 89 pages)
- Expanded VAE
- More detailed DDPM
- New section: physics of diffusion
- and more
Feedback is welcome!
We are pleased to announce plans for a special issue of Signal Processing Magazine focused on the mathematics of deep learning:
https://t.co/5lVaqNDlYP
We look forward to your submissions!
Oldies but goldies: I Daubechies, Orthonormal bases of compactly supported wavelets, 1988. Defines orthogonal wavelet bases which generalize the Haar basis. The construction is a mathematical gem that uses the Bezout theorem. https://t.co/CJPfOns350
It’s been >20 years since I published my first work on multi-frame super-res (SR) w/ Nhat Nguyen and the late great Gene Golub. Here’s my personal story of SR as I’ve experienced it from theory, to practical algorithms, to deployment in product. In a way it’s been my life’s work
I wrote a tutorial on diffusion models for undergrad and grad students. I tried my best to give intuitive explanations for complicated equations.
Your feedback is much appreciated
Thanks to those who suggested various reading materials to me
https://t.co/fWv111nG5M