Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
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Updated
Mar 22, 2021 - Python
Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
Non-parametric Entropy Estimation Toolbox
CorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.
Interpretable data visualizations for understanding how texts differ at the word level
The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory.
Official Implementation of Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (2020)
Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python
A flexible version of CorEx developed for bio-data challenges that handles missing data, continuous/discrete variables, multi-CPU, overlapping structure, and includes visualizations
An open-source library for Python 3 providing tools for analysis and simulation of analog and digital communication systems.
[ICLR 2021] "InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective" by Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu
The HSIC Bottleneck: Deep Learning without Back-Propagation
Framework for Information Theoretical analysis of Electrophysiological data and Statistics
Periodic time series analysis tools based on information theory
A toolkit to boost the productivity of machine learning engineers.
Tensorflow 2 source code for the PI-SAC agent from "Predictive Information Accelerates Learning in RL" (NeurIPS 2020)
Fast, linear version of CorEx for covariance estimation, dimensionality reduction, and subspace clustering with very under-sampled, high-dimensional data
Implementation of Information Dropout
Python Symbolic Information Theoretic Inequality Prover
Easy Nearest Neighbor Estimation of Mutual Information
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