NCC 2021 - Auto-SCMA: Learning Codebook for Sparse Code Multiple Access using Machine Learning

Message passing decoded Hard and Soft for BEC and BSC

Probabilistic modeling through Bayesian inference using PyStan with demonstrative case study experiments from Christopher Bishop's Model-based Machine Learning.

Code to simulate Belief Propagation in the Hopfield model for pattern reconstruction

My very first venture into distributed systems lead me to build this simple message passing algorithm in my most loved language