activity
20192024
most citedNeural Network Coding

9 citations · 9 across the 6 of their papers we have counts for

collaborators

8 papers

cs.IT2024

Two-Stage Decoding Algorithm and Bounds for Group Testing with Prior Statistics

Ayelet C. Portnoy, Amit Solomon, Alejandro Cohen

In this paper, we propose an efficient two-stage decoding algorithm for non-adaptive Group Testing (GT) with general correlated prior statistics. The proposed solution can be appli…

cs.IT2021

DeepNP: Deep Learning-Based Noise Prediction for Ultra-Reliable Low-Latency Communications

Adina Waxman, Nir Shlezinger, Alejandro Cohen

Adaptive network coding schemes provide a promising approach to bridging the gap between high data rates and low delay in real-time streaming applications. However, their effective…

cs.IT2020★ 9 cited

Neural Network Coding

Litian Liu, Amit Solomon, Salman Salamatian +1

In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well…

cs.IT2020

Noise Recycling

Alejandro Cohen, Amit Solomon, Ken R. Duffy +1

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combinatio…

q-bio.QM2020

Multi-Level Group Testing with Application to One-Shot Pooled COVID-19 Tests

Amit Solomon, Alejandro Cohen, Nir Shlezinger +2

A key requirement in containing contagious diseases, such as the Coronavirus disease 2019 (COVID-19) pandemic, is the ability to efficiently carry out mass diagnosis over large pop…

cs.IT2020

Noise Recycling

Alejandro Cohen, Amit Solomon, Ken R. Duffy +1

We introduce Noise Recycling, a method that substantially enhances decoding performance of orthogonal channels subject to correlated noise without the need for joint encoding or de…

cs.IT2020

Soft Maximum Likelihood Decoding using GRAND

Amit Solomon, Ken R. Duffy, Muriel Médard

Maximum Likelihood (ML) decoding of forward error correction codes is known to be optimally accurate, but is not used in practice as it proves too challenging to efficiently implem…

cs.IT2019

5G NR CA-Polar Maximum Likelihood Decoding by GRAND

Ken Duffy, Amit Solomon, Kishori M. Konwar +1

CA-Polar codes have been selected for all control channel communications in 5G NR, but accurate, computationally feasible decoders are still subject to development. Here we report…