365 citations · 463 across the 8 of their papers we have counts for
5 papers · 1 filter
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels
Yihan Jiang, Hyeji Kim, Himanshu Asnani +3
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. Asymptotically…
Improving Federated Learning Personalization via Model Agnostic Meta Learning
Yihan Jiang, Jakub Konečný, Keith Rush +1
Federated Learning (FL) refers to learning a high quality global model based on decentralized data storage, without ever copying the raw data. A natural scenario arises with data c…
DeepTurbo: Deep Turbo Decoder
Yihan Jiang, Hyeji Kim, Himanshu Asnani +3
Present-day communication systems routinely use codes that approach the channel capacity when coupled with a computationally efficient decoder. However, the decoder is typically de…
MIND: Model Independent Neural Decoder
Yihan Jiang, Hyeji Kim, Himanshu Asnani +1
Standard decoding approaches rely on model-based channel estimation methods to compensate for varying channel effects, which degrade in performance whenever there is a model mismat…
BOAssembler: a Bayesian Optimization Framework to Improve RNA-Seq Assembly Performance
Shunfu Mao, Yihan Jiang, Edwin Basil Mathew +1
High throughput sequencing of RNA (RNA-Seq) can provide us with millions of short fragments of RNA transcripts from a sample. How to better recover the original RNA transcripts fro…