Literature Review¶
Theory¶
Gaussianization¶
The original Gaussianization algorithms.
- Gaussianization - Chen & Gopinath - (2000) - PDF
- Nonlinear Extraction of 'Independent Components' of elliptically symmetric densities using radial Gaussianization - Lyu & Simoncelli - Technical Report (2008) - PDF
Applications
- Gaussianization for fast and accurate inference from cosmological data - Schuhman et. al. - (2016) - PDF
- Estimating Information in Earth Data Cubes - Johnson et. al. - EGU 2018
- Multivariate Gaussianization in Earth and Climate Sciences - Johnson et. al. - Climate Informatics 2019 - repo
- Climate Model Intercomparison with Multivariate Information Theoretic Measures - Johnson et. al. - AGU 2019 - slides
- Information theory measures and RBIG for Spatial-Temporal Data analysis - Johnson et. al. - In progress
Things to Think about¶
- A Note on the Evaluation of Generative Models - Theis et. al. - ICLR 2016 - PDF
Journal Articles¶
- Iterative Gaussianization: from ICA to Random Rotations - Laparra et. al. (2011) - IEEE Transactions on Neural Networks
RBIG¶
The most updated Gaussianization algorithm which generalizes the original algorithms. It is more computationally efficient and still very simple to implement.
- Iterative Gaussianization: from ICA to Random Rotations - Laparra et. al. - IEEE TNNs - Paper
Applications
Generalized Divisive Normalization¶
This can be thought of as an approximation to the Gaussianization
- Density Modeling of Images Using a Generalized Normalized Transformation - Balle et al. - ICLR (2016) - arxiv | Lecture | PyTorch | TensorFlow
- End-to-end Optimized Image Compression - Balle et. al. - CVPR (2017) - axriv
- Learning Divisive Normalization in Primary Visual Cortex - Gunthner et. al. - bioarxiv