LiamCattell / optimaltransport
Optimal transport transforms
☆22Updated 6 years ago
Alternatives and similar repositories for optimaltransport:
Users that are interested in optimaltransport are comparing it to the libraries listed below
- Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)☆19Updated 6 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆73Updated 8 years ago
- Gaussian Process Prior Variational Autoencoder☆83Updated 6 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆62Updated last year
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆55Updated 5 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆43Updated 3 years ago
- Stochastic Optimization for Optimal Transport☆22Updated 8 years ago
- L. Chizat, G. Peyré, B. Schmitzer, F-X. Vialard. Scaling Algorithms for Unbalanced Transport Problems. Preprint Arxiv:1607.05816, 2016.☆42Updated 8 years ago
- A Python implementation of Monge optimal transportation☆49Updated last year
- PyTorch implementation of the Covariate-GPLVM☆26Updated 5 years ago
- A matlab toolbox to perform Wasserstein Dictionary Learning or NMF☆32Updated 8 years ago
- Practical sessions for the Optimal Transport and Machine learning course at DS3 2018☆89Updated 6 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆33Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- ☆28Updated 3 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 3 years ago
- Python implementation of smooth optimal transport.☆57Updated 3 years ago
- Code for Sliced Gromov-Wasserstein☆67Updated 5 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Variational Autoencoders & Normalizing Flows Project☆18Updated 8 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"☆29Updated 4 years ago