scikit-mine : pattern mining in Python

Knowledge Graph summarization for anomaly/error detection & completion (WebConf '20)

Minimum Description Length Recurrent Neural Networks (MDLRNNs) in PyTorch

MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".

Minimum Description Length Recurrent Neural Networks

Code for paper "InfoShield: Generalizable Information-Theoretic Human-Trafficking Detection" (ICDE 2021)

The provided program jointly optimizes a multilinear face model and the registration of the face scans used for model training.

Implementation of the genetic algorithm for structural break detection in time series that chooses a piecewise autoregressive model using minimum description length principle

Python implementation of the K2 algorithm for structural learning of Bayesian Networks.

The provided program robustly learns a multilinear face model from databases with missing data, corrupt data, wrong semantic correspondence, and inaccurate vertex correspondence.

Minimum Description Length Hopfield Networks

Seminar paper (@ Technical University Munich) on parameter free clustering of weighted graphs using PaCCo (Parameter-free Clustering by Coding costs)

The framework for finding multiresolution partitions that have homogeneous linear models from multiresolution dataset.

This repository contains Java and C++ implementations of the algorithm GEMPE introduced in the KDD 2020 paper "Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning" by Claudia Plant, Sonja Biedermann and Christian Böhm.

Demonstrating how to use crude MDL to regularize polynomial regression models.

Code of HMG: Heuristic-driven MDL-based Genome sequence compressor

Estimating the parametric complexity (minimum description length) of binary classifiers.

Learning Bayesian Networks with the Complete Minimum Description Length