Aapo Hyvärinen



AISTATS2020: Variational Autoencoders and Nonlinear ICA: A Unifying Framework

JMLR: Neural Empirical Bayes

UAI2019: Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA

AISTATS2019: Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

AISTATS2019: Estimation of Non-Normalized Mixture Models and Clustering Using Deep Representation

NeuroImage: Decoding attentional states for neurofeedback: Mindfulness vs. wandering thoughts

Github: Code for Time-Contrastive Learning


Deep unsupervised learning

[NEW!]  Code for Time-Contrastive Learning

Linear unsupervised learning

FastICA: Fast Independent Component Analysis

ICASSO: Analyzing reliability of independent components

LiNGAM: Causal discovery based on non-Gaussianity

Natural image statistics / visual modelling

Natural Image Statistics package (code for the book);
alternatively the imageica package

Neuroimaging data analysis

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

[Most were programmed by others, but implementing algorithms I have (co-)developed]