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

Last update: Nov 27, 2022

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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)

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

Related tags

Overview

PSML

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

For PSML_IONE

For PSML_ABNE

For PSML_SNNA

For PSML_DeepLink

For PSML_MGCN

For PSML_DALUAP

NOTE:

Owner

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

Related tags

Overview

PSML

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

For PSML_IONE

For PSML_ABNE

For PSML_SNNA

For PSML_DeepLink

For PSML_MGCN

For PSML_DALUAP

NOTE:

Owner

Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks

Drone Task1 - Drone Task1 With Python

Copy Paste positive polyp using poisson image blending for medical image segmentation

Leaderboard and Visualization for RLCard

Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

Codes and pretrained weights for winning submission of 2021 Brain Tumor Segmentation (BraTS) Challenge

A task-agnostic vision-language architecture as a step towards General Purpose Vision

SE3 Pose Interp - Interpolate camera pose or trajectory in SE3, pose interpolation, trajectory interpolation

Implementations for the ICLR-2021 paper: SEED: Self-supervised Distillation For Visual Representation.

AdamW optimizer for bfloat16 models in pytorch.

Adds timm pretrained backbone to pytorch's FasterRcnn model

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Implementation for Paper "Inverting Generative Adversarial Renderer for Face Reconstruction"

Lolviz - A simple Python data-structure visualization tool for lists of lists, lists, dictionaries; primarily for use in Jupyter notebooks / presentations

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