Search Results for author: Ashish Bora

Found 5 papers, 1 papers with code

AmbientGAN: Generative models from lossy measurements

no code implementations ICLR 2018 Ashish Bora, Eric Price, Alexandros G. Dimakis

Generative models provide a way to model structure in complex distributions and have been shown to be useful for many tasks of practical interest.

Compressed Sensing using Generative Models

2 code implementations ICML 2017 Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis

The goal of compressed sensing is to estimate a vector from an underdetermined system of noisy linear measurements, by making use of prior knowledge on the structure of vectors in the relevant domain.

Graphical RNN Models

no code implementations15 Dec 2016 Ashish Bora, Sugato Basu, Joydeep Ghosh

Many time series are generated by a set of entities that interact with one another over time.

Time Series

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