Official code for "A Normalized Gaussian Wasserstein Distance for Tiny Object Detection"
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Updated
Jun 21, 2022 - Python
Official code for "A Normalized Gaussian Wasserstein Distance for Tiny Object Detection"
Optimal transport algorithms for Julia
PyTorch implementation of slicing adversarial network (SAN)
MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
Measure the distance between two spectra/signals using optimal transport and related metrics
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
Functional Optimal Transport: Map Estimation and Domain Adaptation for Functional data
1D Wasserstein Statistical Loss in Pytorch
A thorough review of the paper "Learning Embeddings into Entropic Wasserstein Spaces" by Frogner et al. Includes a reproduction of the results on word embeddings.
Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning - UAI 2021
Discovering Conservation Laws using Optimal Transport and Manifold Learning
LAMDA: Label Matching Deep Domain Adaptation - ICML 2021
Unsupervised Domain Adaptation for Acoustic Scene Classification with Wasserstein Distance
Persistence Diagrams in Julia
Header only C++ implementation of the Wasserstein distance (or earth mover's distance)
My version of cWGAN-gp. Simply my cDCGAN-based but using the Wasserstein Loss and gradient penalty.
Sparse simplex projection-based Wasserstein k-means
OT1D: Discrete Optimal Transport in 1D by Linear Programming
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