Please note the following vision seminar that may be of interest.
---------- Forwarded message --------- From: Avital Shafran avital.shafran@mail.huji.ac.il Date: Tue, Jan 9, 2024 at 8:55 AM Subject: [Vision-Seminar] Sunday 14/1/24 - Tomer Michaeli (Technion), room C320 To: vision-seminar@mail.huji.ac.il, Tomer Michaeli < tomer.m@ee.technion.ac.il>
Dear all,
The next seminar will be given by Prof. Tomer Michaeli from the Technion. The talk will be held in room C320.
Time: Sunday 14/1/24, 10:15 AM.
*Title:* Quantification and Visualization of Uncertainty in Imaging Inverse Problems
*Abstract:*
Uncertainty quantification is crucial for the deployment of image restoration models in safety-critical domains, like biological and medical imaging. To date, methods for uncertainty visualization have mainly focused on per-pixel estimates, which provide limited information. A more natural visualization of uncertainty can be obtained from the principal components (PCs) of the posterior distribution. In this talk I will present methods for predicting the PCs of the posterior, as well as for visualizing the distribution along the space spanned by those PCs, in a single forward pass of a neural network. Our methods are both more accurate and orders of magnitude faster than the naïve approach of applying PCA to posterior samples generated by a conditional generative model. I will illustrate the effectiveness of our approaches on multiple inverse problems in imaging, including denoising, inpainting, super-resolution, colorization, and biological image-to-image translation.
The talk will cover joint works with Elias Nehme, Omer Yair, and Hila Manor.
*Bio:* Tomer Michaeli is an Associate Professor in the Faculty of Electrical and Computer Engineering at the Technion – Israel Institute of Technology. He completed his BSc and PhD degrees at the EE faculty of the Technion in 2005 and 2012, respectively. From 2012 to 2015 he was a postdoctoral fellow in the CS and Applied Math Department at the Weizmann Institute of Science. In 2015 he joined the Technion as a faculty member. His research lies in the fields of Computer Vision and Machine Learning. He is the recipient of several awards, among which are the Krill Prize for Excellence in Scientific Research by the Wolf foundation (2020), the Best Paper Award (Marr Prize) at ICCV 2019, and the Alon Fellowship for Outstanding Young Scientists (2017-2019).