PyTorch implementation of slicing adversarial network (SAN)
-
Updated
May 17, 2024 - Python
PyTorch implementation of slicing adversarial network (SAN)
MS-Mapping: Multi-session LiDAR Mapping with Wasserstein-based Keyframe Selection and Balanced Pose Graph
A Graph Optimal Transport Python Package
Bisimulation Critic for Reinforcement Learning
Code of numerical experiments in Master's thesis [TBD]
Open-set detection using Wasserstein Distance and Spectral Normalisation
Computational optimal transport
Optimization of Stochastic Differential Equation Solver for Particle Data Set Generation using Fast Point Cloud Diffusion (FPCD) model.
Keras-based Implementation for "SARS-CoV-2 Detection: Radiology based Multi-modal Multi-task Framework" (Accepted in 45th IEEE EMBC 2k23)
Persistence Diagrams in Julia
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
OT1D: Discrete Optimal Transport in 1D by Linear Programming
PyTorch Wrapper for Earth-Mover-Distance (EMD) for 3D point cloud regression
Discovering Conservation Laws using Optimal Transport and Manifold Learning
Optimal transport algorithms for Julia
This repository contains some code for demonstrating the application of Wasserstein GANs (WGANs)
This repository contains the code for some blog posts on the Wasserstein metric. For further details, please refer to the corresponding posts.
Investigating the Capability of Generative Adversarial Networks in Capturing Implicit Laws in Physical Systems - Master thesis 2023
Variational Filtering via Wasserstein Gradient Flow
Some code to Get the Optimal relative Transport started. This will be slowly updated if needed.
Add a description, image, and links to the wasserstein-distance topic page so that developers can more easily learn about it.
To associate your repository with the wasserstein-distance topic, visit your repo's landing page and select "manage topics."