hichamjanati / spatio-temporal-alignementsLinks
Spatio-temporal alignements: Optimal transport in space and time
☆48Updated 8 months ago
Alternatives and similar repositories for spatio-temporal-alignements
Users that are interested in spatio-temporal-alignements are comparing it to the libraries listed below
Sorting:
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Gaussian Process Prior Variational Autoencoder☆87Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- ☆51Updated last year
- Python implementation of smooth optimal transport.☆61Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆101Updated 7 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆59Updated 4 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆57Updated 6 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆81Updated 3 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆122Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Pytorch implementation of the Power Spherical distribution☆74Updated last year
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- GyroSPD: Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices☆18Updated 4 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Pytorch implementation for "Particle Flow Bayes' Rule"☆15Updated 6 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆37Updated 5 years ago
- Implementation of the Convolutional Conditional Neural Process☆127Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge☆62Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- ☆125Updated 2 years ago
- Pytorch implementation of Block Neural Autoregressive Flow☆181Updated 4 years ago