atong01 / ot-icnn-minimalLinks
A minimal example of optimal transport with Input Convex Neural Networks in Pytorch
☆24Updated 4 years ago
Alternatives and similar repositories for ot-icnn-minimal
Users that are interested in ot-icnn-minimal are comparing it to the libraries listed below
Sorting:
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆152Updated 2 months ago
- Official PyTorch implementation of NeuralSVD (ICML 2024)☆21Updated last year
- Learning the optimal transport map via input convex neural neworks☆42Updated 5 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆94Updated 3 years ago
- Optimal Transport for Machine Learners☆43Updated 2 months ago
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆82Updated 8 months ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆25Updated 2 years ago
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆52Updated last year
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- ☆12Updated last year
- PyTorch implementation of Stein Variational Gradient Descent☆47Updated 2 years ago
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆43Updated 3 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆88Updated last year
- ☆53Updated 3 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated 2 years ago
- ☆36Updated 4 years ago
- Benchmarks for Model-Based Optimization☆96Updated last year
- ☆46Updated 2 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Updated 3 years ago
- A Python package to learn the Koopman operator.☆65Updated 3 weeks ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 11 months ago
- ☆13Updated 2 years ago
- Manifold Learning by Mixture Models of VAEs for Inverse Problems☆19Updated last year
- Tutorial on amortized optimization for learning to optimize over continuous domains☆249Updated 3 months ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Mutual information estimators and benchmark☆56Updated 3 months ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 3 years ago
- [ICLR 2022] Path integral sampler☆52Updated 2 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆65Updated last year