Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters

Related tags

Deep Learningmot
Overview

MOT

Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters (von Lindheim, 2022). Using the emd OT solver from the Python Optimal Transport (POT) package, which is a wrapper of this network simplex solver, which, in turn, is based on an implementation in the LEMON C++ library.

Installation

  1. Download the code or clone the Github repository with
git clone https://github.com/jvlindheim/mot.git
  1. For the code in mot.py, there is the following dependencies: numpy, matplotlib.pyplot, the cdist function from scipy.spatial.distance and the emd function from the POT library. You can install them e.g. using pip via
pip install --user numpy scipy matplotlib POT

If you want to run the demo notebook, you will also need to have Jupyter Notebook or JupyterLab installed.

Owner
Johannes von Lindheim
Johannes von Lindheim
Use deep learning, genetic programming and other methods to predict stock and market movements

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

Linda MacPhee-Cobb 386 Jan 03, 2023
Python code to generate art with Generative Adversarial Network

GAN_Canvas_Maker Generating Art using Generative Adversarial Network (GAN) Python code to generate art with Generative Adversarial Network: https://to

Jonny Banana 10 Aug 22, 2022
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning

Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu

Costas Mavromatis 21 Dec 03, 2022
Code for Mining the Benefits of Two-stage and One-stage HOI Detection

Status: Archive (code is provided as-is, no updates expected) PPO-EWMA [Paper] This is code for training agents using PPO-EWMA and PPG-EWMA, introduce

OpenAI 33 Dec 15, 2022
Code for "The Box Size Confidence Bias Harms Your Object Detector"

The Box Size Confidence Bias Harms Your Object Detector - Code Disclaimer: This repository is for research purposes only. It is designed to maintain r

Johannes G. 24 Dec 07, 2022
This repository holds the code for the paper "Deep Conditional Gaussian Mixture Model forConstrained Clustering".

Deep Conditional Gaussian Mixture Model for Constrained Clustering. This repository holds the code for the paper Deep Conditional Gaussian Mixture Mod

17 Oct 30, 2022
A tiny, pedagogical neural network library with a pytorch-like API.

candl A tiny, pedagogical implementation of a neural network library with a pytorch-like API. The primary use of this library is for education. Use th

Sri Pranav 3 May 23, 2022
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

76 Jan 03, 2023
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin

Deepak Pathak 829 Dec 31, 2022
Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works

GDAP Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works Environment Python (verified: v3.8) CUDA

45 Oct 29, 2022
Instance-based label smoothing for improving deep neural networks generalization and calibration

Instance-based Label Smoothing for Neural Networks Pytorch Implementation of the algorithm. This repository includes a new proposed method for instanc

Mohamed Maher 1 Aug 13, 2022
Users can free try their models on SIDD dataset based on this code

SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p

Yuzhi ZHAO 2 May 20, 2022
Official implementation of our paper "LLA: Loss-aware Label Assignment for Dense Pedestrian Detection" in Pytorch.

LLA: Loss-aware Label Assignment for Dense Pedestrian Detection This project provides an implementation for "LLA: Loss-aware Label Assignment for Dens

35 Dec 06, 2022
Amazing-Python-Scripts - 🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.

📑 Introduction A curated collection of Amazing Python scripts from Basics to Advance with automation task scripts. This is your Personal space to fin

Avinash Ranjan 1.1k Dec 29, 2022
Implementation of neural class expression synthesizers

NCES Implementation of neural class expression synthesizers (NCES) Installation Clone this repository: https://github.com/ConceptLengthLearner/NCES.gi

NeuralConceptSynthesis 0 Jan 06, 2022
A bare-bones Python library for quality diversity optimization.

pyribs Website Source PyPI Conda CI/CD Docs Docs Status Twitter pyribs.org GitHub docs.pyribs.org A bare-bones Python library for quality diversity op

ICAROS 127 Jan 06, 2023
D2Go is a toolkit for efficient deep learning

D2Go D2Go is a production ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms. W

Facebook Research 744 Jan 04, 2023
Official implementation of CVPR2020 paper "Deep Generative Model for Robust Imbalance Classification"

Deep Generative Model for Robust Imbalance Classification Deep Generative Model for Robust Imbalance Classification Xinyue Wang, Yilin Lyu, Liping Jin

9 Nov 01, 2022
DeepMReye: magnetic resonance-based eye tracking using deep neural networks

DeepMReye: magnetic resonance-based eye tracking using deep neural networks

73 Dec 21, 2022
An end-to-end project on customer segmentation

End-to-end Customer Segmentation Project Note: This project is in progress. Tools Used in This Project Prefect: Orchestrate workflows hydra: Manage co

Ocelot Consulting 8 Oct 06, 2022