Software
[Mostly programmed by collaborators, but implementing algorithms I have (co-)developed]
Deep unsupervised learning
Structured Nonlinear ICA using JAX
ICE-BEeM using Pytorch
iVAE using PyTorch
Independent Innovation Analysis using PyTorch
Nonlinear ICA using HMM using JAX
Time-Contrastive Learning using TensorFlow 1 (a bit old)
Linear unsupervised learning
FastICA: Fast Independent Component Analysis (for Matlab, see scikit-learn for a good Python version)
ICASSO: Analyzing reliability of independent components (for Matlab, see here for Python)
LiNGAM: Causal discovery based on non-Gaussianity (for various systems: Python, R, Matlab)
Shared Independent Component Analysis for multi-view data (in Python)
Natural image statistics / visual modelling (for Matlab)
Natural Image Statistics package (code for the book);
alternatively the imageica package
Neuroimaging data analysis (for Matlab)
SpeDeBox: Decoding EEG/MEG using spectral infomation
OCF: Analysing variability (nonstationarity) of connectivity
ISCTEST: Testing independent components
Fourier-ICA: Improved ICA by time-frequency transforms
|
