PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)
☆323Dec 9, 2024Updated last year
Alternatives and similar repositories for ppnp
Users that are interested in ppnp are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).☆374Nov 6, 2022Updated 3 years ago
- PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)☆128Apr 5, 2022Updated 4 years ago
- ☆309Jul 17, 2022Updated 3 years ago
- ☆142Jul 9, 2023Updated 2 years ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆849Dec 13, 2021Updated 4 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Official Implementation of AdaGCN (ICLR 2021)☆64Jan 3, 2022Updated 4 years ago
- Graph Filter Neural Network (ICPR'20)☆48Aug 6, 2020Updated 5 years ago
- Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020☆401Jun 17, 2024Updated last year
- Framework for evaluating Graph Neural Network models on semi-supervised node classification task☆495Dec 5, 2018Updated 7 years ago
- PyTorch implementation of "Simple and Deep Graph Convolutional Networks"☆363Jul 9, 2020Updated 5 years ago
- AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning☆58May 22, 2019Updated 7 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Oct 11, 2022Updated 3 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆476Dec 7, 2022Updated 3 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆200Mar 6, 2024Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- [ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)☆294Apr 21, 2021Updated 5 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆357Jun 12, 2025Updated 11 months ago
- Inductive graph-based matrix completion (IGMC) from "M. Zhang and Y. Chen, Inductive Matrix Completion Based on Graph Neural Networks, IC…☆367Apr 9, 2023Updated 3 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆124Jun 27, 2019Updated 6 years ago
- Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"☆76Feb 2, 2023Updated 3 years ago
- links to conference publications in graph-based deep learning☆5,072Updated this week
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆211Jul 6, 2023Updated 2 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆68Oct 11, 2022Updated 3 years ago
- ☆101Mar 22, 2021Updated 5 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆191Mar 22, 2022Updated 4 years ago
- Measuring and Improving the Use of Graph Information in Graph Neural Networks☆83Jul 25, 2024Updated last year
- [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…☆508Aug 12, 2022Updated 3 years ago
- Strategies for Pre-training Graph Neural Networks☆1,063Jul 29, 2023Updated 2 years ago
- The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""☆529Mar 25, 2021Updated 5 years ago
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆166Aug 30, 2022Updated 3 years ago
- Benchmark datasets, data loaders, and evaluators for graph machine learning☆2,089May 6, 2025Updated last year
- PyTorch implementation of "Scalable Graph Neural Networks via Bidirectional Propagation"☆26Nov 3, 2020Updated 5 years ago
- How Powerful are Graph Neural Networks?☆1,283Jul 1, 2021Updated 4 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding☆438Nov 5, 2020Updated 5 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Jun 9, 2021Updated 5 years ago
- Implementation for Simple Spectral Graph Convolution in ICLR 2021☆84Oct 7, 2022Updated 3 years ago
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆668Nov 1, 2022Updated 3 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆70Nov 29, 2023Updated 2 years ago
- Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"☆308May 12, 2023Updated 3 years ago
- An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).☆406Nov 6, 2022Updated 3 years ago