Neural Cover Selection for Image Steganography
Neural Cover Selection for Image Steganography This blog post is written as an overview and summary of our recent work... Continue
Task-Aware Distributed Source Coding under Dynamic Bandwidth
Deep learning based distributed compression for efficient data transmission in multi-sensor networks Reducing communication overload in multi-sensor networks is becoming... Continue
The Fundamental Limits of Prompt Compression
This blog post is written as an overview and summary of our NeurIPS 2024 paper, Fundamental Limits of Prompt Compression:... Continue
Learning Non-Linear Polar codes via Deep Learning
Setup : Channel coding We consider the problem of reliably communicating a binary message over a noisy channel. The effect... Continue
Estimation of Rate-Distortion Function for Computing with Decoder Side Information
In the ever-evolving landscape of data science, the quest for efficient data compression methods remains a critical challenge. Compression not... Continue
Learning context-dependent autoencoders for CSI feedback
A Motivating Question: How do we cluster different datasets into different groups? When developing data-driven machine learning models for a... Continue
Generating High Dimensional Wireless Channels using Diffusion Models
Significant advancements in deep neural networks have led to developments in wireless communication. However, these deep learning-based methods require extensive... Continue
Learning Codes for Interference Channels
Interference Channels A two-user interference channel is a canonical model for multiple one-to-one communications, where two transmitters wish to communicate... Continue
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