The code is to reproduce the numerical results in Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models.

ML_RI_GAMP.m is the code for a 2-layer network with ReLU activation, Gaussian prior, Gaussian observation and Gaussian or Beta spectrum, and ML_RI_GAMP.m generates its SE.

Some parts of the code including free_cum_calc.m that calculates free cumulants of weight matrices are from Marco Mondelli's implementation of his work Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing. Some parts are from https://github.com/GAMPTeam/vampyre.