Efficient compression of correlated data is essential to minimize
commun...
In modern communication systems with feedback, there are increasingly mo...
In this paper, we introduce a neural-augmented decoder for Turbo codes c...
In the decoding of linear block codes, it was shown that noticeable gain...
A critical aspect of reliable communication involves the design of codes...
The two-user interference channel is a model for multi one-to-one
commun...
Meta-learning provides a popular and effective family of methods for
dat...
Distributed source coding is the task of encoding an input in the absenc...
In this paper, we consider a communication system where a sender sends
m...
We respond to [1] which claimed that "Modulo-SK scheme outperforms Deepc...
Convolutional neural networks (CNNs) have recently become the
state-of-t...
Neural architecture search (NAS) enables researchers to automatically ex...
Recent works in single-image perceptual super-resolution (SR) have
demon...
This paper uses Coanda Effect to reduce motors, the source of noise, and...
Automatic speech recognition (ASR) via call is essential for various
app...
Neural architecture search (NAS) has been very successful at outperformi...
Designing codes that combat the noise in a communication medium has rema...
Present-day communication systems routinely use codes that approach the
...
Network compression reduces the computational complexity and memory
cons...
Designing channel codes under low latency constraints is one of the most...
The design of codes for communicating reliably over a statistically well...
Low-rank decomposition plays a central role in accelerating convolutiona...
Coding theory is a central discipline underpinning wireline and wireless...
Discovering a correlation from one variable to another variable is of
fu...