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Jonathan Tamir

2 accepted papers

2021

Hyperbolic graph embedding with enhanced semi-implicit variational inference.

AISTATS 2021poster

Efficient modeling of relational data arising in physical, social, and information sciences is challenging due to complicated dependencies within the data. In this work we build off of semi-implicit graph variational auto-encoders to capture higher order statistics in a low-dimensional graph latent…

2021

Robust Compressed Sensing MRI with Deep Generative Priors

NeurIPS 2021poster

The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep generative priors can be powerful tools for solving inverse problems. However, to date this framework has been empirically successful only on certain datasets (for example, human faces and MNIST digits), and it is known to perform…