dhruvdcoder / HyperA
Started as a Team Project for CS690D at UMass Amherst, now turning into pytorch implementation of hyperbolic neural networks using Poincare Ball model. [Final report](https://github.com/dhruvdcoder/HyperA/tree/master/report)
☆12Updated 2 years ago
Alternatives and similar repositories for HyperA:
Users that are interested in HyperA are comparing it to the libraries listed below
- ☆12Updated 3 years ago
- ☆26Updated 6 years ago
- ☆30Updated last year
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year
- ☆17Updated 5 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 4 years ago
- Source code for Noise-Contrastive Estimation for Multivariate Point Processes (NeurIPS 2020).☆15Updated 4 years ago
- Transformers are Graph Neural Networks!☆51Updated 4 years ago
- Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks☆13Updated 4 years ago
- ☆12Updated 4 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 4 years ago
- ☆42Updated 7 years ago
- MATLAB implementation of linear support vector classification in hyperbolic space☆20Updated 6 years ago
- Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.☆45Updated last year
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆42Updated last year
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆35Updated 4 years ago
- ☆17Updated 2 years ago
- ☆10Updated 2 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆21Updated 4 years ago
- Repository for ICLR'23 Long-tailed Learning Requires Feature Learning☆10Updated last year
- Fast graph-regularized matrix factorization☆20Updated last year
- Low Rank Global Attention for Graph Neural Networks☆12Updated 4 years ago
- ☆29Updated 2 years ago
- ☆35Updated 5 years ago
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 3 years ago
- Rep the Set: Neural Networks for Learning Set Representations☆29Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆54Updated 3 years ago
- A comprehensive collection of GNN works in NeurIPS 2019.☆21Updated 5 years ago
- Deep Graph Mapper: Seeing Graphs through the Neural Lens☆55Updated last year
- Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"☆42Updated last year