Heterogeneous Deep Graph Infomax

Last update: Oct 31, 2022

Overview

Heterogeneous-Deep-Graph-Infomax

Parameter Setting:

HDGI-A:

Node-level dimension: 16
Attention head: 4
Semantic-level attention vector: 8
learning rate: 0.02

HDGI-C:

Node-level dimension: 64
Semantic-level attention vector: 8
learning rate: 0.02

GAT:

Node-level dimension: 16
Attention head: 4
learning rate: 0.005
Drop out ratio: 0.6

GCN:

Hidden-unit dimension: 64
learning rate: 0.01
Drop out ratio: 0.5

RGCN:

Hidden-unit dimension: 16
learning rate: 0.01
Drop out ratio: 0

Metapath2Vec:

Embedding dimension: 100
learning rate: 0.01
negative-samples: 5
Window: 1

HAN:

Node-level dimension: 16
Attention head: 4
Semantic-level dimension: 8
learning rate: 0.005
Node-level Drop out ratio: 0.6
Semantic-level Drop out ratio: 0.6

Deepwalk:

Number of walks per node: 10
Dimensions of word embeddings: 128
Length of random walk: 30
Window size for skipgram: 5

DGI:

Hidden-unit dimension: 64
learning rate: 0.001
Drop out ratio: 0

Owner

GitHub Repository

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Heterogeneous Deep Graph Infomax

Related tags

Overview

Heterogeneous-Deep-Graph-Infomax

HDGI-A:

HDGI-C:

GAT:

GCN:

RGCN:

Metapath2Vec:

HAN:

Deepwalk:

DGI:

Owner

Applying curriculum to meta-learning for few shot classification

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A package for "Procedural Content Generation via Reinforcement Learning" OpenAI Gym interface.

This is the Pytorch implementation of Progressive Attentional Manifold Alignment.

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Offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation

This repo is customed for VisDrone.

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Heterogeneous Deep Graph Infomax

Related tags

Overview

Heterogeneous-Deep-Graph-Infomax

HDGI-A:

HDGI-C:

GAT:

GCN:

RGCN:

Metapath2Vec:

HAN:

Deepwalk:

DGI:

Owner

Applying curriculum to meta-learning for few shot classification

Pytorch implementation of set transformer

A package for "Procedural Content Generation via Reinforcement Learning" OpenAI Gym interface.

​ This is the Pytorch implementation of Progressive Attentional Manifold Alignment.

Distributed Arcface Training in Pytorch

Offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation

This repo is customed for VisDrone.

Keyhole Imaging: Non-Line-of-Sight Imaging and Tracking of Moving Objects Along a Single Optical Path

A PyTorch-centric hybrid classical-quantum machine learning framework

Deep Learning Training Scripts With Python

Official implementation of deep-multi-trajectory-based single object tracking (IEEE T-CSVT 2021).

Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.

Good Classification Measures and How to Find Them

git《Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction》(ECCV 2020) GitHub:

Official implementation of cosformer-attention in cosFormer: Rethinking Softmax in Attention

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

KIND: an Italian Multi-Domain Dataset for Named Entity Recognition

Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

Deep Learning agent of Starcraft2, similar to AlphaStar of DeepMind except size of network.

Code for DeepCurrents: Learning Implicit Representations of Shapes with Boundaries

This is the Pytorch implementation of Progressive Attentional Manifold Alignment.