gabsens / Learning-Embeddings-into-Entropic-Wasserstein-Spaces-ENSAE
A thorough review of the paper "Learning Embeddings into Entropic Wasserstein Spaces" by Frogner et al. Includes a reproduction of the results on word embeddings.
☆22Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for Learning-Embeddings-into-Entropic-Wasserstein-Spaces-ENSAE
- MATLAB implementation of linear support vector classification in hyperbolic space☆21Updated 6 years ago
- Code accompanying our paper at AISTATS 2020☆21Updated 3 years ago
- Rep the Set: Neural Networks for Learning Set Representations☆27Updated 4 years ago
- Python implementation of smooth optimal transport.☆56Updated 3 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆35Updated 4 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆62Updated 4 years ago
- Keras implementation of Deep Wasserstein Embeddings☆46Updated 6 years ago
- ☆65Updated 3 months ago
- [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution☆36Updated 3 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆53Updated 3 years ago
- Hyperbolic Neural Networks, pytorch☆84Updated 5 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆58Updated 3 years ago
- Official PyTorch (Lightning) implementation of the NeurIPS 2020 paper "Efficient Marginalization of Discrete and Structured Latent Variab…☆28Updated 3 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆42Updated last year
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated last year
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10Updated 6 years ago
- LP-SparseMAP: Differentiable sparse structured prediction in coarse factor graphs☆41Updated last year
- Code for Reparameterizable Subset Sampling via Continuous Relaxations, IJCAI 2019.☆52Updated last year
- Ancestral Gumbel-Top-k Sampling☆23Updated 4 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆26Updated 4 years ago
- ☆45Updated 4 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 2 years ago
- Code for the NeurIPS 2018 paper "On Controllable Sparse Alternatives to Softmax"☆22Updated 5 years ago
- Implementation of the "Poincare Glove: Hyperbolic word embeddings" paper☆85Updated 3 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆39Updated 4 years ago
- Layerwise Relevance Visualization in Convolutional Text Graph Classifiers☆12Updated 3 years ago
- Gromov-Wasserstein Alignment of Embeddings☆64Updated 3 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Group-conditional DRO to alleviate spurious correlations☆15Updated 3 years ago