Permute Me Softly: Learning Soft Permutations for Graph Representations

Overview

Permute Me Softly: Learning Soft Permutations for Graph Representations

Code for the paper Permute Me Softly: Learning Soft Permutations for Graph Representations.

Requirements

Code is written in Python 3.7 and requires:

  • PyTorch 1.9
  • PyTorch Geometric 2.0
  • NetworkX 2.2

Run the model

You can specify the dataset and the hyperparameters in the main.py file, and then execute:

python main.py

Cite

Please cite our paper if you use this code:

@article{nikolentzos2021permute,
  title={Permute Me Softly: Learning Soft Permutations for Graph Representations},
  author={Nikolentzos, Giannis and Dasoulas, George and Vazirgiannis, Michalis},
  journal={arXiv preprint arXiv:2110.01872},
  year={2021}
}

Provided for academic use only

Owner
Giannis Nikolentzos
Giannis Nikolentzos
StrongSORT: Make DeepSORT Great Again

StrongSORT StrongSORT: Make DeepSORT Great Again StrongSORT: Make DeepSORT Great Again Yunhao Du, Yang Song, Bo Yang, Yanyun Zhao arxiv 2202.13514 Abs

369 Jan 04, 2023
A pytorch reprelication of the model-based reinforcement learning algorithm MBPO

Overview This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Mo

Xingyu Lin 93 Jan 05, 2023
Credit fraud detection in Python using a Jupyter Notebook

Credit-Fraud-Detection - Credit fraud detection in Python using a Jupyter Notebook , using three classification models (Random Forest, Gaussian Naive Bayes, Logistic Regression) from the sklearn libr

Ali Akram 4 Dec 28, 2021
Efficient Multi Collection Style Transfer Using GAN

Proposed a new model that can make style transfer from single style image, and allow to transfer into multiple different styles in a single model.

Zhaozheng Shen 2 Jan 15, 2022
(EI 2022) Controllable Confidence-Based Image Denoising

Image Denoising with Control over Deep Network Hallucination Paper and arXiv preprint -- Our frequency-domain insights derive from SFM and the concept

Images and Visual Representation Laboratory (IVRL) at EPFL 5 Dec 18, 2022
Evaluation toolkit of the informative tracking benchmark comprising 9 scenarios, 180 diverse videos, and new challenges.

Informative-tracking-benchmark Informative tracking benchmark (ITB) higher diversity. It contains 9 representative scenarios and 180 diverse videos. m

Xin Li 15 Nov 26, 2022
Official PyTorch implementation of the paper: DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample

DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape

Eliahu Horwitz 393 Dec 22, 2022
Simultaneous Demand Prediction and Planning

Simultaneous Demand Prediction and Planning Dependencies Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML Data POI: data/poi Road network

Yizong Wang 1 Sep 01, 2022
eXPeditious Data Transfer

xpdt: eXPeditious Data Transfer About xpdt is (yet another) language for defining data-types and generating code for serializing and deserializing the

Gianni Tedesco 3 Jan 06, 2022
A library for differentiable nonlinear optimization.

Theseus A library for differentiable nonlinear optimization built on PyTorch to support constructing various problems in robotics and vision as end-to

Meta Research 1.1k Dec 30, 2022
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques

Data Science 45-min Intros Every week*, our data science team @Gnip (aka @TwitterBoulder) gets together for about 50 minutes to learn something. While

Scott Hendrickson 1.6k Dec 31, 2022
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.

Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst

Alex 39 Oct 08, 2022
Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks

This is the code associated with the paper Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks, published at CVPR 2020.

Thomas Roddick 219 Dec 20, 2022
Light-Head R-CNN

Light-head R-CNN Introduction We release code for Light-Head R-CNN. This is my best practice for my research. This repo is organized as follows: light

jemmy li 835 Dec 06, 2022
Instant-nerf-pytorch - NeRF trained SUPER FAST in pytorch

instant-nerf-pytorch This is WORK IN PROGRESS, please feel free to contribute vi

94 Nov 22, 2022
Generate indoor scenes with Transformers

SceneFormer: Indoor Scene Generation with Transformers Initial code release for the Sceneformer paper, contains models, train and test scripts for the

Chandan Yeshwanth 110 Dec 06, 2022
Building blocks for uncertainty-aware cycle consistency presented at NeurIPS'21.

UncertaintyAwareCycleConsistency This repository provides the building blocks and the API for the work presented in the NeurIPS'21 paper Robustness vi

EML Tübingen 19 Dec 12, 2022
Multiview 3D object detection on MultiviewC dataset through moft3d.

Voxelized 3D Feature Aggregation for Multiview Detection [arXiv] Multiview 3D object detection on MultiviewC dataset through VFA. Introduction We prop

Jiahao Ma 20 Dec 21, 2022
Mitsuba 2: A Retargetable Forward and Inverse Renderer

Mitsuba Renderer 2 Documentation Mitsuba 2 is a research-oriented rendering system written in portable C++17. It consists of a small set of core libra

Mitsuba Physically Based Renderer 2k Jan 07, 2023
A Bayesian cognition approach for belief updating of correlation judgement through uncertainty visualizations

Overview Code and supplemental materials for Karduni et al., 2020 IEEE Vis. "A Bayesian cognition approach for belief updating of correlation judgemen

Ryan Wesslen 1 Feb 08, 2022