Code for KHGT model, AAAI2021

Last update: Nov 29, 2022

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Deep Learning KHGT

Overview

KHGT

Code for KHGT accepted by AAAI2021

Please unzip the data files in Datasets/ first.

To run KHGT on Yelp data, use

python labcode_yelp.py

For MovieLens data, use the following command to train

python labcode_ml10m.py --data ml10m --graphSampleN 1000 --save_path XXX

and use this command to test with larger sampled sub-graphs

python labcode_ml10m.py --data ml10m --graphSampleN 5000 --epoch 0 --load_model XXX

For Online Retail data, use this command to train

python labcode_retail.py --data retail --graphSampleN 15000 --reg 1e-1 --save_path XXX

and also load the model to test it with larger sampled sub-graphs

python labcode_retail.py --data retail --graphSampleN 30000 --epoch 0 --load_model XXX

Owner

GitHub Repository

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Code for KHGT model, AAAI2021

Related tags

Overview

KHGT

Owner

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Code for KHGT model, AAAI2021

Related tags

Overview

KHGT

Owner

List some popular DeepFake models e.g. DeepFake, FaceSwap-MarekKowal, IPGAN, FaceShifter, FaceSwap-Nirkin, FSGAN, SimSwap, CihaNet, etc.

A PyTorch Implementation of the Luna: Linear Unified Nested Attention

Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection

Zero-Cost Proxies for Lightweight NAS

Feature extraction made simple with torchextractor

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An image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testingAn image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testing

Data loaders and abstractions for text and NLP

Scalable, event-driven, deep-learning-friendly backtesting library

Wordle-solver - Wordle answer generation program in python

The source code and dataset for the RecGURU paper (WSDM 2022)

Chinese Mandarin tts text-to-speech 中文 (普通话) 语音 合成 , by fastspeech 2 , implemented in pytorch, using waveglow as vocoder,

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising

Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection

JAX-based neural network library

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Select, weight and analyze complex sample data

Deep Learning tutorials in jupyter notebooks.

Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)

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