LUOyk1999 / DAGformerLinks
[NeurIPS 2023] Implementation of "Transformers over Directed Acyclic Graphs"
☆72Updated 6 months ago
Alternatives and similar repositories for DAGformer
Users that are interested in DAGformer are comparing it to the libraries listed below
Sorting:
- A graph neural network tailored to directed acyclic graphs that outperforms conventional GNNs by leveraging the partial order as strong i…☆135Updated last year
- ☆16Updated last year
- The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…☆314Updated last year
- Official implementation of our VQ-GNN paper (NeurIPS2021)☆38Updated 4 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆267Updated 3 years ago
- A graph transformer framework☆78Updated 3 years ago
- Representing Long-Range Context for Graph Neural Networks with Global Attention☆130Updated 3 years ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆161Updated 2 years ago
- ☆156Updated 4 years ago
- "Do We Need Anisotropic Graph Neural Networks?" at ICLR 2022☆33Updated 3 years ago
- ☆57Updated 4 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆26Updated 3 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆83Updated 2 years ago
- [ICLR 2025 Spotlight] LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs☆23Updated 10 months ago
- PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepte…☆143Updated 10 months ago
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆167Updated last year
- [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…☆137Updated 3 years ago
- Official Pytorch Implementation of GraphiT☆110Updated 4 years ago
- ☆177Updated 2 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆95Updated last year
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆125Updated 3 years ago
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆99Updated last year
- Code for our paper "Attending to Graph Transformers"☆92Updated 2 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆97Updated 3 years ago
- [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)☆105Updated 2 years ago
- MagNet graph convolutional network☆41Updated last year
- Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021☆41Updated 4 years ago
- Parameterized Explainer for Graph Neural Network☆140Updated last year
- ☆37Updated 4 years ago
- Dynamic Graph Benchmark☆87Updated 2 years ago