khainb / 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 2 years ago
Alternatives and similar repositories for Mini-batch-OT:
Users that are interested in Mini-batch-OT are comparing it to the libraries listed below
- Distributional Sliced-Wasserstein distance code☆49Updated 8 months ago
- Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"☆46Updated 2 years ago
- Keypoint-Guided Optimal Transport (NeurIPS 2022)☆23Updated last year
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- Official PyTorch implementation for paper: Energy-Based Sliced Wasserstein Distance☆18Updated last month
- [ICML2023] InfoOT: Information Maximizing Optimal Transport☆40Updated last year
- Implementation of our ICLR2023 paper "Spherical-Sliced Wasserstein"☆13Updated last year
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- ☆10Updated 2 years ago
- ☆14Updated 4 years ago
- Code for Neural Manifold Clustering and Embedding☆59Updated 3 years ago
- C-GMVAE: Gaussian Mixture VAE with Contrastive Learning for Multi-Label Classification☆48Updated last year
- Experiments to reproduce results in Interventional Causal Representation Learning.☆24Updated 2 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 2 years ago
- Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".☆9Updated 7 months ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆37Updated last year
- ☆17Updated last year
- Robust Optimal Transport code☆43Updated 2 years ago
- This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…☆21Updated 2 years ago
- ☆10Updated 2 months ago
- This repository contains the code for our paper "Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguo…☆40Updated last year
- Implementation of the Gumbel-Sigmoid distribution in PyTorch.☆20Updated 2 years ago
- Quantile risk minimization☆24Updated 8 months ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 5 years ago
- ☆19Updated 3 years ago
- source code for paper "Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models"☆24Updated 9 months ago
- [NeurIPS 2024] BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models☆26Updated 2 months ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago