In the AI for TSP competition we try to solve optimization problems using machine learning.

Related tags

Deep Learningreinforcement-learningsurrogate-based-optimization
Overview

AI for TSP Competition

Goal

In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted at the Data Science meets Optimization workshop at IJCAI21 and consists of two tracks:

  • Online supervised learning using surrogate models
  • Reinforcement learning

The goal of this competition is to strengthen the relation between the machine learning field and the optimization field. You can learn more about the competition here.

Prizes

Cash prizes will be announced soon!

Timeline

  • May 7: Start of the tryout period
  • May 21: Competition start
  • July 5: Submission deadline (validation)
  • July 12: Submission deadline (test)
  • August 9: Winners are contacted privately
  • August 21/22: Public announcement of winners

Whitepaper

For more details about the competition, please refer to this document.

Official Documentation

Check out our Documentation

Announcements

Check out our Announcements

FAQ

Check out our FAQ

Slack Channel

Check out our Slack Channel

Dependencies

  • Python=3.8 (should be OK with v >= 3.6)
  • PyTorch=1.8 (track 2 only)
  • Numpy=1.20
  • bayesian-optimization=1.1.0 (track 1 only)
  • Pandas=1.2.4
  • Conda=4.8.4 (optional)

Please check environment.yml

Acknowledgments

Special thanks to https://github.com/pemami4911/neural-combinatorial-rl-pytorch for the implemetation of Neural CO used as part of this repository.

Owner
Paulo da Costa
Paulo da Costa
GitHub Repository https://www.tspcompetition.com/
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

U-GAT-IT — Official PyTorch Implementation : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Imag

Hyeonwoo Kang 2.4k Jan 04, 2023
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022
NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

5 Nov 03, 2022
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data

SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Au

14 Nov 28, 2022
Posterior predictive distributions quantify uncertainties ignored by point estimates.

Posterior predictive distributions quantify uncertainties ignored by point estimates.

DeepMind 177 Dec 06, 2022
Pytorch implementation of Implicit Behavior Cloning.

Implicit Behavior Cloning - PyTorch (wip) Pytorch implementation of Implicit Behavior Cloning. Install conda create -n ibc python=3.8 pip install -r r

Kevin Zakka 49 Dec 25, 2022
Adversarial examples to the new ConvNeXt architecture

Adversarial examples to the new ConvNeXt architecture To get adversarial examples to the ConvNeXt architecture, run the Colab: https://github.com/stan

Stanislav Fort 19 Sep 18, 2022
Code accompanying the paper on "An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers" published at NeurIPS, 2021

Code for "An Empirical Investigation of Domian Generalization with Empirical Risk Minimizers" (NeurIPS 2021) Motivation and Introduction Domain Genera

Meta Research 15 Dec 27, 2022
Use .csv files to record, play and evaluate motion capture data.

Purpose These scripts allow you to record mocap data to, and play from .csv files. This approach facilitates parsing of body movement data in statisti

21 Dec 12, 2022
Code repository for our paper regarding the L3D dataset.

The Large Labelled Logo Dataset (L3D): A Multipurpose and Hand-Labelled Continuously Growing Dataset Website: https://lhf-labs.github.io/tm-dataset Da

LHF Labs 9 Dec 14, 2022
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Mask R-CNN for Object Detection and Segmentation This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bound

Matterport, Inc 22.5k Jan 04, 2023
A hue shift helper for OBS

obs-hue-shift A hue shift helper for OBS This is a repo based on the really nice script Hegemege made. The original script can be found https://gist.g

Alexis Tyler 1 Jan 10, 2022
High-quality implementations of standard and SOTA methods on a variety of tasks.

Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo

Google 1.1k Dec 30, 2022
This repository contains a re-implementation of the code for the CVPR 2021 paper "Omnimatte: Associating Objects and Their Effects in Video."

Omnimatte in PyTorch This repository contains a re-implementation of the code for the CVPR 2021 paper "Omnimatte: Associating Objects and Their Effect

Erika Lu 728 Dec 28, 2022
Spectralformer: Rethinking hyperspectral image classification with transformers

The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.

Danfeng Hong 104 Jan 04, 2023
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022

Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema

Pgxo20 24 Jan 02, 2023
Lane follower: Lane-detector (OpenCV) + Object-detector (YOLO5) + CAN-bus

Lane Follower This code is for the lane follower, including perception and control, as shown below. Environment Hardware Industrial Camera Intel-NUC(1

Siqi Fan 3 Jul 07, 2022
PyTorch implementation of residual gated graph ConvNets, ICLR’18

Residual Gated Graph ConvNets April 24, 2018 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbress

Xavier Bresson 112 Aug 10, 2022
Least Square Calibration for Peer Reviews

Least Square Calibration for Peer Reviews Requirements gurobipy - for solving convex programs GPy - for Bayesian baseline numpy pandas To generate p

Sigma <a href=[email protected]"> 1 Nov 01, 2021
A framework for analyzing computer vision models with simulated data

3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:

3DB 112 Jan 01, 2023