- TOULOUSE, FRANCE
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A webcam-based 3x3x3 rubik's cube solver written in Python 3 and OpenCV.
High-Performance Symbolic Regression in Python and Julia
PPO implementation of the DRL agent used in the paper "Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case"
Attention based model for learning to solve different routing problems
Discrete Optimization is a python library to ease the definition and re-use of discrete optimization problems and solvers.
Solve Rubik's Cube in less than 19 moves on average with Python.
The AIPlan4EU Unified Planning Library
Implementation of "Learning Combinatorial Optimization Algorithms over Graphs"
Implementation for the paper "Target Cuts from Relaxed Decision Diagrams"
Implementation of the paper "Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning".
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
A Python Library for modeling combinatorial constrained problems
Awesome machine learning for combinatorial optimization papers.
Implementation of local search-based algorithms for solving SAT and Max-SAT in Python
Exact Combinatorial Optimization with Graph Convolutional Neural Networks (NeurIPS 2019)
DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)
Implementation of basic CDCL-based SAT solver in Python
A Python (re-)implementation of some known knowledge compilers
A Reinforcement Learning Approach to the Orienteering Problem with Time Windows
LaTeX templates de l'INSA Toulouse
Repository for benchmarking graph neural networks
Fit interpretable models. Explain blackbox machine learning.
AI framework for Reinforcement Learning, Automated Planning and Scheduling
Must-read papers on graph neural networks (GNN)