Python implementation of block decomposition method for approximating algorithmic complexity

Repository for the Online Algorithmic Complexity Calculator

Minimum Description Length Recurrent Neural Networks (MDLRNNs) in PyTorch

Minimum Description Length Recurrent Neural Networks

Repository for the Online Algorithmic Complexity Calculator

(TODO) actually callable javascript lambdas of infinitely threadable (potentially massively-multiplayer) godel-like-numbering-secure low latency neuralnet approximation of hypercomputation of the iota combinator sparse-emulating debugger breakpoints of itself, in javascript lambdas, such as naming every possible lambda by a 256 bit merkle id

Computational predictions of protein attributes associated with COVID-19 using Data Science techniques

Estimation of the robustness of networks to attacks directed using Kolmogorov complexity as estimated by the Block Decomposition Method.

A small Julia library for calculating the normalized compression distance.

Minimum Description Length Hopfield Networks

In Kolmogorov's sense of complexity, conditional complexity allows to take some background knowledge into account for description complexity. Can this concept be applied to image recognition? I did a quick experiment to try to highlight this process in the context of image recognition.

DNA Sequencing Analysis using compression algorithms

Python code to implement an efficient approach to unsupervised OOD detection with VAE

Write the shortest possible programs to generate given strings

Python implementation of block decomposition method for approximating algorithmic complexity

Measuring linguistic complexity through information theory

A CLI utility to handle data as binary string