hhcho / hyplinear
MATLAB implementation of linear support vector classification in hyperbolic space
☆20Updated 6 years ago
Alternatives and similar repositories for hyplinear:
Users that are interested in hyplinear are comparing it to the libraries listed below
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆55Updated 3 years ago
- Python implementation of smooth optimal transport.☆57Updated 3 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆35Updated 4 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆42Updated last year
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆61Updated 4 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- Rep the Set: Neural Networks for Learning Set Representations☆29Updated 4 years ago
- ☆12Updated 5 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year
- Code accompanying our paper at AISTATS 2020☆21Updated 4 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 6 years ago
- A comprehensive collection of GNN works in NeurIPS 2019.☆21Updated 5 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆21Updated 5 years ago
- A thorough review of the paper "Learning Embeddings into Entropic Wasserstein Spaces" by Frogner et al. Includes a reproduction of the re…☆22Updated 5 years ago
- ☆45Updated 4 years ago
- Official implementation (learning part) for paper: Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models☆18Updated 8 months ago
- ☆24Updated 3 years ago
- Hyperbolic Neural Networks, pytorch☆86Updated 5 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆55Updated 5 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated last year
- Humans understand novel sentences by composing meanings and roles of core language components. In contrast, neural network models for nat…☆27Updated 4 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 4 years ago
- [ICLR 2019] Learning Representations of Sets through Optimized Permutations☆36Updated 5 years ago
- ☆26Updated 6 years ago
- ☆13Updated 4 years ago
- Learning and Reasoning with Graph-Structured Data (ICML 2019 Workshop)☆26Updated 5 years ago
- Learning Tree structures and Tree metrics☆23Updated 7 months ago