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UID:2025-11-19-berthy-feng@cail.columbia.edu
DTSTAMP:20260823T060715Z
DTSTART:20251119T180000Z
DTEND:20251119T190000Z
SUMMARY:Vision Seminar: Berthy Feng - Taming Priors for Scientific Computa
 tional Imaging
LOCATION:CSB 488
DESCRIPTION:Computational imaging aims to visualize scientific phenomena b
 eyond the reach of conventional optics by incorporating assumptions\, or p
 riors\, about the object being imaged. In the age of AI\, the priors avail
 able to us are more sophisticated than ever. However\, it is yet unclear h
 ow to use these priors rigorously\, especially when using imaging in the s
 cientific process. The main challenge of computational imaging for science
  is discerning when to use what prior and how. The art of imaging lies in 
 deciding the correct balance of assumptions to obtain trustworthy and info
 rmative images. Once the prior has been decided\, the question is how to i
 ncorporate it rigorously.\n\nIn this talk\, I will present my previous wor
 k on building principled routes for incorporating data-driven and physics-
 based priors. On the data-driven side\, I will show results of re-imaginin
 g the famous M87 black hole from real data with score-based priors. On the
  physics-based side\, I will show how we have tackled extremely under-dete
 rmined imaging problems by enforcing physics constraints\, including the p
 roblem of single-viewpoint dynamic tomography of emission near a black hol
 e. In the intersection of AI and physics\, I will present neural approxima
 te mirror maps\, a way to enforce physics constraints on generative models
 . I will then discuss future directions for further taming priors so that 
 we can rigorously create\, interpret\, and act upon scientific images.\n\n
 https://cail.columbia.edu/events/2025-11-19-berthy-feng
URL:https://cail.columbia.edu/events/2025-11-19-berthy-feng
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