Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

Related tags

Deep LearningPSML
Overview

PSML

paper: Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

PSML_IONE,PSML_ABNE,PSML_DEEPLINK,PSML_SNNA:

numpy==1.14<br>
networkx==2.0<br>
scipy==0.19.1<br>
tensorflow>=1.12.1<br>
gensim==3.0.1<br>
scikit-learn==0.19.0<br>

PSML_DALUAP,PSML_MGCN:

python >= 3.6<br>
pytorch >= 0.4<br>
numpy  1.18.0<br>
tqdm<br>
networkx >2.0<br>

support data comes from :https://github.com/ChuXiaokai/CrossMNA
query data comes from :https://github.com/ColaLL/IONE
, https://github.com/ColaLL/AcrossNetworkEmbeddingDiversity

For PSML_IONE

   first run PSML_IONE.py
   second run Four.py
   getPrecision--should run emd_to_ione_emd.py and emd_to_ione_emd_t.py

For PSML_ABNE

   first run PSML_ABNE.py
   second run Four.py
   getPrecision--should run emd_to_ione_emd.py and emd_to_ione_emd_t.py

For PSML_SNNA

   use deepwalk or line get pre_data
   run PSML_SNNA.py

For PSML_DeepLink

   run embedding.py to use word2vec get pre_data
   run PSML_Deeplink.py

For PSML_MGCN

   run PSML_MGCN.py

For PSML_DALUAP

   run PSML_DALUAP.py

NOTE:

Method of adding pseudo node, Take two pseudo anchors, which are connected to each other, such as subnetwork file:

        node      node
         1          2
         3(anchor)  4

You need change it to:

        node      node
         1          2
         3(anchor)  4
         3          5(pse)
         3          6(pse)
         5(pse)     3
         6(pse)     3
         5(pse)     6(pse)
         6(pse)     5(pse)
         
CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation

CDGAN CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation CDGAN Implementation in PyTorch This is the imple

Kancharagunta Kishan Babu 6 Apr 19, 2022
Reviving Iterative Training with Mask Guidance for Interactive Segmentation

This repository provides the source code for training and testing state-of-the-art click-based interactive segmentation models with the official PyTorch implementation

Visual Understanding Lab @ Samsung AI Center Moscow 406 Jan 01, 2023
Towards Boosting the Accuracy of Non-Latin Scene Text Recognition

Convolutional Recurrent Neural Network + CTCLoss | STAR-Net Code for paper "Towards Boosting the Accuracy of Non-Latin Scene Text Recognition" Depende

Sanjana Gunna 7 Aug 07, 2022
School of Artificial Intelligence at the Nanjing University (NJU)School of Artificial Intelligence at the Nanjing University (NJU)

F-Principle This is an exercise problem of the digital signal processing (DSP) course at School of Artificial Intelligence at the Nanjing University (

Thyrix 5 Nov 23, 2022
Code Release for the paper "TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation"

TriBERT This repository contains the code for the NeurIPS 2021 paper titled "TriBERT: Full-body Human-centric Audio-visual Representation Learning for

UBC Computer Vision Group 8 Aug 31, 2022
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!

Designing a Practical Degradation Model for Deep Blind Image Super-Resolution Kai Zhang, Jingyun Liang, Luc Van Gool, Radu Timofte Computer Vision Lab

Kai Zhang 804 Jan 08, 2023
2021 credit card consuming recommendation

2021 credit card consuming recommendation

Wang, Chung-Che 7 Mar 08, 2022
HyperCube: Implicit Field Representations of Voxelized 3D Models

HyperCube: Implicit Field Representations of Voxelized 3D Models Authors: Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemysław Spurek [Pap

Magdalena Proszewska 3 Mar 09, 2022
Optimizaciones incrementales al problema N-Body con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámbito de HPC.

Python HPC Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámb

Andrés Milla 12 Aug 04, 2022
Automatic caption evaluation metric based on typicality analysis.

SeMantic and linguistic UndeRstanding Fusion (SMURF) Automatic caption evaluation metric described in the paper "SMURF: SeMantic and linguistic UndeRs

Joshua Feinglass 6 Jan 09, 2022
ComputerVision - This repository aims at realized easy network architecture

ComputerVision This repository aims at realized easy network architecture Colori

DongDong 4 Dec 14, 2022
MultiLexNorm 2021 competition system from ÚFAL

ÚFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5 David Samuel & Milan Straka Charles University Faculty of

ÚFAL 13 Jun 28, 2022
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion This repo intends to release code for our work: Zhaoyang Lyu*, Zhifeng

Zhaoyang Lyu 68 Jan 03, 2023
PyTorch implementation of Self-supervised Contrastive Regularization for DG (SelfReg)

SelfReg PyTorch official implementation of Self-supervised Contrastive Regularization for Domain Generalization (SelfReg, https://arxiv.org/abs/2104.0

64 Dec 16, 2022
Custom TensorFlow2 implementations of forward and backward computation of soft-DTW algorithm in batch mode.

Batch Soft-DTW(Dynamic Time Warping) in TensorFlow2 including forward and backward computation Custom TensorFlow2 implementations of forward and backw

19 Aug 30, 2022
A collection of educational notebooks on multi-view geometry and computer vision.

Multiview notebooks This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks incl

Max 65 Dec 09, 2022
Official code for the ICLR 2021 paper Neural ODE Processes

Neural ODE Processes Official code for the paper Neural ODE Processes (ICLR 2021). Abstract Neural Ordinary Differential Equations (NODEs) use a neura

Cristian Bodnar 50 Oct 28, 2022
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks

Efficient Sharpness-aware Minimization for Improved Training of Neural Networks Code for “Efficient Sharpness-aware Minimization for Improved Training

Angusdu 32 Oct 18, 2022
CCP dataset from Clothing Co-Parsing by Joint Image Segmentation and Labeling

Clothing Co-Parsing (CCP) Dataset Clothing Co-Parsing (CCP) dataset is a new clothing database including elaborately annotated clothing items. 2, 098

Wei Yang 434 Dec 24, 2022
An unofficial styleguide and best practices summary for PyTorch

A PyTorch Tools, best practices & Styleguide This is not an official style guide for PyTorch. This document summarizes best practices from more than a

IgorSusmelj 1.5k Jan 05, 2023