no code implementations • 18 Aug 2020 • Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
DeepCode is designed and evaluated for the AWGN channel with (potentially delayed) uncoded output feedback.
no code implementations • 8 Oct 2022 • Hanqiu Chen, Yahya Alhinai, Yihan Jiang, Eunjee Na, Cong Hao
A variety of dynamic graph neural networks designed from algorithmic perspectives have succeeded in incorporating temporal information into graph processing.
1 code implementation • 30 Nov 2018 • Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
Designing channel codes under low-latency constraints is one of the most demanding requirements in 5G standards.
1 code implementation • 14 Feb 2019 • Shunfu Mao, Yihan Jiang, Edwin Basil Mathew, Sreeram Kannan
High throughput sequencing of RNA (RNA-Seq) can provide us with millions of short fragments of RNA transcripts from a sample.
2 code implementations • 27 Sep 2019 • Yihan Jiang, Jakub Konečný, Keith Rush, Sreeram Kannan
We present FL as a natural source of practical applications for MAML algorithms, and make the following observations.
1 code implementation • NeurIPS 2018 • Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
The design of codes for communicating reliably over a statistically well defined channel is an important endeavor involving deep mathematical research and wide-ranging practical applications.
3 code implementations • ICLR 2018 • Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
We show that creatively designed and trained RNN architectures can decode well known sequential codes such as the convolutional and turbo codes with close to optimal performance on the additive white Gaussian noise (AWGN) channel, which itself is achieved by breakthrough algorithms of our times (Viterbi and BCJR decoders, representing dynamic programing and forward-backward algorithms).
1 code implementation • NeurIPS 2019 • Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
Designing codes that combat the noise in a communication medium has remained a significant area of research in information theory as well as wireless communications.
1 code implementation • 6 Mar 2019 • Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
We focus on Turbo codes and propose DeepTurbo, a novel deep learning based architecture for Turbo decoding.