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ailab

aisnakegame

C++写的一个AI贪吃蛇

attention-learn-to-route

Attention based model for learning to solve different routing problems

auto.js-vscode-extension

A simple development plugin for Auto.js.

beagle

A generic C++ framework for evolutionary computation

bug-free-invention

cevrp

chinese-std-gb-t-7714-related-csl

GB/T 7714相关的csl以及Zotero使用技巧及教程。

cuopt-resources

A collection of NVIDIA cuOpt samples and other resources

cvrp

This repository contains algorithms in C++ to solve the Capacitated Vehicle Routing Problem (cvrp).

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

deap

Distributed Evolutionary Algorithms in Python

discrete-optimization

Discrete Optimization is a python library to ease the definition and re-use of discrete optimization problems and solvers.

engine-sim

Combustion engine simulator that generates realistic audio.

english-level-up-tips

An advanced guide to learn English which might benefit you a lot 🎉 . 可能是让你受益匪浅的英语进阶指南。

evohyp-python

A python port of EvoHyp

evrp

evrp-iterated-local-search

evrp_std

GA + Tabu search solve CVRP and EVRP problem

finetune-transformer-lm

Code and model for the paper "Improving Language Understanding by Generative Pre-Training"

ga_vrp_gpu

ga_vrp_mgpu

A version of the GA algorithm for the VRP running on multiple GPUs

ga_vrp_mod

An update and improvement of the GA for VRP on the GPU

geatpy

Evolutionary algorithm toolbox and framework with high performance for Python

gphhucarp

This repository contains a Java implementation of the Uncertain Capacitated Arc Routing Problem environment. Several solution methods are implemented, most revolving around the Genetic Programming Hyper Heuristic technique developed by Dr. Yi Mei and Jordan MacLachlan from the Victoria University of Wellington.

gplearn

Genetic Programming in Python, with a scikit-learn inspired API

gppt

gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

gpt-3

GPT-3: Language Models are Few-Shot Learners

gpt-gnn

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"