matlab代码abs-Universal-Graph-Embedding-Neural-Network:论文代码学习借助迁移学

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  • 2022-05-20 08:20
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matlab代码abs 论文代码:借助迁移学习学习通用图神经网络嵌入 通用图嵌入神经网络论文: 包装要求: 火炬 学习 scipy 休蒂尔 Comet_ml(可选,可重复实验所需) matlab.engine(可选,计算 FGSD Graph Kernel 所需) 运行主脚本: Python火车/train_ugd.py
Universal-Graph-Embedding-Neural-Network-master.zip
  • Universal-Graph-Embedding-Neural-Network-master
  • dataloader
  • graph_dataloader.py
    3.3KB
  • read_graph_datasets.py
    5.5KB
  • data.py
    2.5KB
  • graph_datasets.py
    6.3KB
  • read_qm8_dataset.py
    4.7KB
  • utils
  • fast_wl_kernel.py
    5.4KB
  • compute_fgsd_features.py
    1KB
  • fast_fgsd_features.py
    1.6KB
  • compute_wl_kernel.py
    3.3KB
  • utils.py
    4.4KB
  • read_sdf_file.py
    1.4KB
  • config
  • params_universal_graph_embedding_model.py
    907B
  • hyperopt
  • run_train_hyperopt.py
    2.8KB
  • torch_dgl
  • models
  • model_universal_graph_embedding.py
    4KB
  • universal_graph_encoder.py
    1.4KB
  • layers
  • ugd_input_layer.py
    1KB
  • graph_capsule_layer.py
    1.2KB
  • train
  • train_ugd.py
    24KB
  • README.md
    1.8KB
内容介绍
[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-collab)](https://paperswithcode.com/sota/graph-classification-on-collab?p=190910086) [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-imdb-m)](https://paperswithcode.com/sota/graph-classification-on-imdb-m?p=190910086) [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-proteins)](https://paperswithcode.com/sota/graph-classification-on-proteins?p=190910086) [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-dd)](https://paperswithcode.com/sota/graph-classification-on-dd?p=190910086) [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-imdb-b)](https://paperswithcode.com/sota/graph-classification-on-imdb-b?p=190910086) [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-ptc)](https://paperswithcode.com/sota/graph-classification-on-ptc?p=190910086) [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/190910086/graph-classification-on-enzymes)](https://paperswithcode.com/sota/graph-classification-on-enzymes?p=190910086) # Paper Code: Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning Universal-Graph-Embedding-Neural-Network Paper: https://arxiv.org/abs/1909.10086 ## Package Requirements: pytorch sklearn scipy shutil comet_ml (optional, required for reproducible experiments) matlab.engine (optional, required for computing FGSD Graph Kernel) ## Running main script: python train/train_ugd.py
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