UT-Austin-Data-Science-Group / Mini-batch-OT
A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, color transfer, and gradient flow.
☆37Updated last year
Alternatives and similar repositories for Mini-batch-OT:
Users that are interested in Mini-batch-OT are comparing it to the libraries listed below
- Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"☆44Updated 2 years ago
- Distributional Sliced-Wasserstein distance code☆49Updated 6 months ago
- Official PyTorch implementation for paper: Energy-Based Sliced Wasserstein Distance☆18Updated 11 months ago
- Implementation of our ICLR2023 paper "Spherical-Sliced Wasserstein"☆13Updated 11 months ago
- [ICML2023] InfoOT: Information Maximizing Optimal Transport☆40Updated last year
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆43Updated last year
- ☆10Updated 2 years ago
- It is a repo which allows to compute all divergences derived from the theory of entropically regularized, unbalanced optimal transport. I…☆28Updated 2 years ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆35Updated 10 months ago
- Keypoint-Guided Optimal Transport (NeurIPS 2022)☆21Updated last year
- ☆10Updated last year
- C-GMVAE: Gaussian Mixture VAE with Contrastive Learning for Multi-Label Classification☆47Updated last year
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆21Updated 4 years ago
- The repository contains reproducible PyTorch source code of our paper Generative Modeling with Optimal Transport Maps, ICLR 2022.☆57Updated 2 years ago
- ☆17Updated last year
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 2 years ago
- Learning Autoencoders with Relational Regularization☆45Updated 4 years ago
- This repository is the implementation of Deep Dirichlet Process Mixture Models (UAI 2022)☆13Updated 2 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- ☆18Updated 3 years ago
- Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".☆9Updated 4 months ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated 2 years ago
- The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".☆12Updated 3 years ago
- Quantile risk minimization☆24Updated 5 months ago
- Code for ECML/PKDD paper: "LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport"☆15Updated 3 years ago
- Code for Neural Manifold Clustering and Embedding☆57Updated 2 years ago
- ☆17Updated 2 years ago
- ☆12Updated last year
- Experiments to reproduce results in Interventional Causal Representation Learning.☆25Updated last year