TinnitusReconstructor
Reverse correlation using linear regression and compressed sensing for uncovering the psychoacoustic tinnitus spectrum
l0
Scalable reinforcement learning pipeline for general-purpose agents. Build and train agents using the Notebook Agent (NB-Agent) in a flexible environment. 🐙🚀
compressedsensing.jl
Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian learning, and basis pursuit.
machine-learning-threshold-displacement-energy-dataset
Public dataset and analysis scripts from the manuscript "Machine Learning-Driven Analytical Models for Threshold Displacement Energy Prediction in Materials." Includes data for monoatomic and polyatomic materials, metadata, and example workflows for analysis and visualization.
tinnitus-reconstruction
Reconstruct high-dimensional spectral representations of tinnitus using reverse correlation