355 citations · 730 across the 16 of their papers we have counts for
5 papers · 1 filter
Beyond Effective Sample Size: Effective Number of Proposals for Adaptive Importance Sampling
Ali Mousavi, Victor Elvira
Population-based adaptive importance sampling (AIS) methods use a set of proposal densities to approximate complex target distributions. Their performance is commonly assessed thro…
Unsupervised Learning with Stein's Unbiased Risk Estimator
Christopher A. Metzler, Ali Mousavi, Reinhard Heckel +1
Learning from unlabeled and noisy data is one of the grand challenges of machine learning. As such, it has seen a flurry of research with new ideas proposed continuously. In this w…
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks
Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
In this paper we develop a novel computational sensing framework for sensing and recovering structured signals. When trained on a set of representative signals, our framework learn…
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
Christopher A. Metzler, Ali Mousavi, Richard G. Baraniuk
Compressive image recovery is a challenging problem that requires fast and accurate algorithms. Recently, neural networks have been applied to this problem with promising results.…
Learning to Invert: Signal Recovery via Deep Convolutional Networks
Ali Mousavi, Richard G. Baraniuk
The promise of compressive sensing (CS) has been offset by two significant challenges. First, real-world data is not exactly sparse in a fixed basis. Second, current high-performan…