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Accel Brain Code ⭐ 289

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 proces

Pygmtools ⭐ 227

A library of Python graph matching solvers.

Graph Convnet Tsp ⭐ 157

Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (INFORMS Annual Meeting Session 2019)

Learning Tsp ⭐ 53

Code for the paper 'Learning TSP Requires Rethinking Generalization' (CP 2021)

Sinkhorn Policy Gradient.pytorch ⭐ 29

Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"

Neurips2021 Ml4co Kida ⭐ 23

1st Solution For NeurIPS 2021 Competition on ML4CO Dual Task

End2end Job Shop Scheduling Cp ⭐ 16

An end to end reinforcement learning approach with a reinforcement learning environment modeled as a CP model

Learning Paradigms For Tsp ⭐ 10

Code for the paper 'On Learning Paradigms for the Travelling Salesman Problem' (NeurIPS 2019 Graph Representation Learning Workshop)

Gnn For Combinatorial Optimization ⭐ 8

JAX + Flax implementation of "Combinatorial Optimization with Physics-Inspired Graph Neural Networks" by Schuetz et al.

Geometric Deep Learning Models for Vehicle Routing Problem

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