Invertible Neural Networks and Inverse Problems

Online lecture on Invertible Neural Networks as priors for inverse problems in imaging. This lecture is from Northeastern University's CS 7180 Spring 2020 class on Special Topics in Artificial Intelligence, taught by Paul Hand.

The notes are available at: http://khoury.northeastern.edu/home/hand/teaching/cs7180-spring-2020/lecture12-invertible-neural-networks-and-inverse-problems.pdf

The papers mentioned are:

NICE - Laurent Dinh, David Krueger, and Yoshua Bengio. "Nice: Non-linear independent components estimation." https://arxiv.org/abs/1410.8516

Real-NVP - Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio. "Density estimation using real nvp." https://arxiv.org/abs/1605.08803

Glow - Diederik Kingma, and Prafulla Dhariwal. "Glow: Generative flow with invertible 1x1 convolutions." In Advances in Neural Information Processing Systems, pp. 10215-10224. 2018. https://arxiv.org/abs/1807.03039

Asim et al. - Muhammad Asim, Ali Ahmed, and Paul Hand. "Invertible generative models for inverse problems: mitigating representation error and dataset bias." https://arxiv.org/abs/1905.11672

Whang et al. - Jay Whang, Qi Lei, and Alexandros G. Dimakis. "Compressed Sensing with Invertible Generative Models and Dependent Noise." https://arxiv.org/abs/2003.08089

Ardizzone et al. - Lynton Ardizzone, Jakob Kruse, Sebastian Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, and Ullrich Köthe. "Analyzing inverse problems with invertible neural networks." https://arxiv.org/abs/1808.04730

Видео Invertible Neural Networks and Inverse Problems канала Paul Hand