deeprank-gnn
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DeepRank-GNN:
Overview
Motivations
Installation
Tutorial:
Creating Graphs
Training a module
In short
Use DeepRank-GNN paper’s pretrained model
Advanced
API
Graph and Graph Generator
Neural Network Training Evaluation and Test
deeprank-gnn
Welcome to DeepRank-GNN’s documentation!
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Welcome to DeepRank-GNN’s documentation!
DeepRank-GNN:
Overview
1) Graph generation
2) Model Training
Motivations
Installation
Via Python Package
Via GitHub
Tutorial:
Creating Graphs
Generate your graphs
Add your target values
Docking benchmark mode
Training a module
1. Select node and edge features
2. Select the target (benchmarking mode)
3. Select hyperparameters
4. Load the network
5. Train the model
6. Analysis
7. Save the model/network
8. Test the model on an external dataset
In short
Use DeepRank-GNN paper’s pretrained model
Advanced
Design your own GNN layer
Design your own neural network architecture
Use your GNN architecture in Deeprank-GNN
API
Graph and Graph Generator
Graphs
Residue Graphs
Graph Generator
Parrallel Graph Generator
Neural Network Training Evaluation and Test
Neural Network
Indices and tables
Index
Module Index
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