Enhancing Differentiability in Image Reconstruction Models

Karen Ullrich is a Research Scientist at FAIR. Her research focuses on the intersection of information theory and probabilistic machine learning and deep learning. Karen's PhD thesis is titled "A coding perspective on deep latent variable models", which she completed in 2020 at The University of Amsterdam. We discuss information theory & the minimum description length principle, along with her work in the thesis on compression and communication. Episode notes: https://cs.nyu.edu/~welleck/episode28.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview