PowerWalk
Graph ranking processor
A system for efficiently computing personalized page rank vectors on large graphs using distributed indexing and online querying
Personalized PageRank (PPR) on GraphLab PowerGraph
15 stars
2 watching
3 forks
Language: C++
last commit: about 8 years ago
Linked from 1 awesome list
graph-algorithmsgraph-processingpagerank-algorithmrandom-walk
Related projects:
Repository | Description | Stars |
---|---|---|
| An implementation of PageRank algorithm for weighted graphs in Go. | 85 |
| An implementation of PageRank and TextRank algorithms in Ruby. | 75 |
| Implementations of a graph neural network model for personalized graph classification | 321 |
| An implementation of a neural network architecture designed to process graph-structured data | 58 |
| An implementation of learnable graph convolutional networks for efficient graph processing | 46 |
| An implementation of an algorithm for learning graph representations from network data | 106 |
| An implementation of an algorithm for learning trajectory representations in temporal graphs | 18 |
| A framework for parallelizing and distributing graph computations to scale large-scale algorithms | 148 |
| A PyTorch implementation of a graph neural network model that learns personalized node representations | 367 |
| An implementation of a deep learning algorithm for graph data | 270 |
| An implementation of a deep learning algorithm to generate node embeddings in graphs | 322 |
| A PyTorch implementation of a semi-supervised graph classification model that learns hierarchical representations from labeled and unlabeled graph data. | 209 |
| A solver for optimizing quadratic programs in deep learning and other fields. | 691 |
| A framework for large-scale graph processing using Erlang. | 384 |
| A library for distributing work across machines using parallel processing | 106 |