Search Packages

ortools

Google's Operations Research tools:

rl4co

A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)

fjsplib

Python package to read and write instances for the flexible job shop problem.

submodlib-py

Summarize Massive Datasets using Submodular Optimization

aegypti

Aegypti: Approximate Clique Solver

accelbrainbeat

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

pydbm

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

qqa

Quasi-Quantum Annealing (QQA): a GPU solver for combinatorial & spin-glass optimisation — PyTorch library + live Streamlit dashboard. ICLR 2025.

numberpartitioning

Pure Python solver for the multi-way partition problem

pysummarization

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

jinete

High Performance solving suite for the Pickup and Delivery Problem and its related extensions.

pyqlearning

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

geco

Generators for Combinatorial Optimization

tspgrasp

A Greedy Randomized Adaptive Search Procedure (GRASP) for the Traveling Salesman Problem (TSP)

accel-brain-base

accel-brain-base is a basic library of the Deep Learning for rapid development at low cost. This library makes it possible to design and implement deep learning, which must be configured as a complex system, by combining a plurality of functionally differentiated modules such as a Deep Boltzmann Machines(DBMs), an Auto-Encoder, an Encoder/Decoder based on Long Short-Term Memory(LSTM), a Convolutional Auto-Encoder(CAE), and Transformer.

hallelujah

Hallelujah: Approximate Vertex Cover Solver

flowty

Network optimisation solver

pygan

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

gyozas

Modern Python Library for Reinforcement Learning for Combinatorial Optimization using Gym Environment

graph-stitcher

This tool is a little framework to determine possiblemerges between two graphs based on a set of requiredadditional relationships (aka as stitches / edges).

pycomposer

pycomposer is Python library for Algorithmic Composition or Automatic Composition based on the stochastic music theory and the Statistical machine learning problems. Especialy, this library provides apprication of the Algorithmic Composer based on Generative Adversarial Networks(GANs) and Conditional Generative Adversarial Networks(Conditional GANs).

jssenv

An optimized OpenAi gym's environment to simulate the Job-Shop Scheduling problem.

tspy

An optimization package for the traveling salesman problem

lp-comp

Python library for coordinated planning in two-level systems, finding compromise solutions between a Center and Elements using mathematical models & a GUI.