73 citations · 160 across the 33 of their papers we have counts for
7 papers · 1 filter
Inference with Deep Generative Priors in High Dimensions
Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan +2
Deep generative priors offer powerful models for complex-structured data, such as images, audio, and text. Using these priors in inverse problems typically requires estimating the…
Input-Output Equivalence of Unitary and Contractive RNNs
M. Emami, M. Sahraee-Ardakan, S. Rangan +1
Unitary recurrent neural networks (URNNs) have been proposed as a method to overcome the vanishing and exploding gradient problem in modeling data with long-term dependencies. A ba…
Power Efficient Discontinuous Reception in THz and mmWave Wireless Systems
Syed Hashim Ali Shah, Sundar Aditya, Sourjya Dutta +2
Discontinuous reception (DRX), where a user equip-ment (UE) temporarily disables its receiver, is a critical power saving feature in modern cellular systems. DRX is likely tobe par…
High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence
Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash A. Amini +2
We consider the problem of estimating the parameters of a multivariate Bernoulli process with auto-regressive feedback in the high-dimensional setting where the number of samples a…
Towards 6G Networks: Use Cases and Technologies
Marco Giordani, Michele Polese, Marco Mezzavilla +2
Reliable data connectivity is vital for the ever increasingly intelligent, automated and ubiquitous digital world. Mobile networks are the data highways and, in a fully connected,…
Asymptotics of MAP Inference in Deep Networks
Parthe Pandit, Mojtaba Sahraee, Sundeep Rangan +1
Deep generative priors are a powerful tool for reconstruction problems with complex data such as images and text. Inverse problems using such models require solving an inference pr…