RingBDStack / HypDiffLinks
This repository is the official implementation of "Hyperbolic Geometric Latent Diffusion Model for Graph Generation (HypDiff)" accepted by the research tracks of International Conference on Machine Learning 2024 (ICML 2024).
☆25Updated 7 months ago
Alternatives and similar repositories for HypDiff
Users that are interested in HypDiff are comparing it to the libraries listed below
Sorting:
- EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling☆55Updated last year
- Official implementation for 'Sparse denoising diffusion for large graph generation'☆59Updated last year
- Official Code Repository for the paper "Graph Generation with Diffusion Mixture" (ICML 2024).☆31Updated last year
- Official Repository for NeurIPS 2024 Paper Unifying Generation and Prediction on Graphs with Latent Graph Diffusion☆30Updated 5 months ago
- Directional diffusion models☆38Updated 7 months ago
- Official Pytorch implementation of NeuralWalker☆33Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆98Updated last year
- Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion Models☆22Updated last year
- Permutation-Invariant Autoregressive Diffusion (NeurIPS 2024)☆15Updated 8 months ago
- An implementation of the Autoregressive Diffusion Model for Graph Generation from [Kong et al. 2023]☆35Updated 4 months ago
- A Quasi-Wasserstein Loss for Learning Graph Neural Networks (QW loss)☆10Updated last year
- Pytorch implementation of ICML-2024 "Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching"☆24Updated 11 months ago
- [ECCV'22] Equivariant Hypergraph Neural Networks, in PyTorch☆30Updated 2 years ago
- Code for ICLR'24 Paper "Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks"☆10Updated last year
- Reference implementation of the paper "Efficient and Scalable Graph Generation through Iterative Local Expansion"☆13Updated last year
- Code for GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts☆16Updated 5 months ago
- Official Code Repository for the paper "Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations" (I…☆170Updated last year
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆44Updated last year
- ☆204Updated last year
- [NeurIPS'23] Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. Haotao Wang, Ziyu Jiang, Yuning Y…☆49Updated last year
- Implementation for the paper: GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation☆27Updated 2 years ago
- The official implementation of the ICML'24 paper "A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer".☆41Updated 2 months ago
- ☆30Updated 5 months ago
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆21Updated last year
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆45Updated 9 months ago
- ☆29Updated last year
- Official PyTorch implementation of SGRL in 'Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering' …☆26Updated 4 months ago
- Rex Ying's Ph.D. Thesis, Stanford University☆42Updated 2 years ago
- ☆35Updated last year
- The official implementation of ``CKGConv: General Graph Convolution with Continuous Kernels'' (ICML 2024)☆26Updated 10 months ago