ChengzijunAixiaoli / PPMMLinks
Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]
☆15Updated 4 years ago
Alternatives and similar repositories for PPMM
Users that are interested in PPMM are comparing it to the libraries listed below
Sorting:
- Official code for the ICLR 2021 paper Neural ODE Processes☆73Updated 3 years ago
- ☆12Updated last year
- Learning the optimal transport map via input convex neural neworks☆42Updated 5 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 10 months ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- ☆38Updated 5 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆53Updated 5 years ago
- ☆15Updated 2 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆34Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆54Updated last year
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- Refining continuous-in-depth neural networks☆42Updated 3 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated last year
- A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).☆21Updated 10 months ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated 2 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 4 years ago
- Differentiable DAG Sampling (ICLR 2022)☆37Updated 3 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 3 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆56Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆26Updated 5 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆34Updated 3 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago