Pytorch-geometeric implementation for TKDE'2023 paper: Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity Interactions @ARTICLE{chen2023dvgga, author={Chen, Han and ...

The proposed model, based on a denoising graph autoencoder (DGAE), regards missing joints as noise corrupted information and aims to reconstruct them to be close to their original coordinates. When ...

By leveraging convolutional neural networks and molecular dynamics simulations, we have developed a denoising autoencoder (DAE) capable of postprocessing experimental ChromSTEM images to provide ...

Run the script below to get results on ZhangDDI dataset. python main.py --second-gcn-dimensions 256 --num_epoch 600 --learning_rate 0.001 --beta2 1 --train_ratio 0.6 --val_ratio 0.2 --test_ratio 0.2 - ...