Master project: Bures-Wasserstein barycenters
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Updated
May 16, 2024 - MATLAB
Master project: Bures-Wasserstein barycenters
Geometrical Layers for Pytorch Neural Networks
Riemannian Adaptive Optimization Methods with pytorch optim
A C++ library of Markov Chain Monte Carlo (MCMC) methods
Algorithms for the approximation of an embedding for Markov chains.
Implementation of Deep SPDNet in pytorch
Code implementations of the methods discussed in Generalized Fiducial Inference on Differentiable Manifolds by A. Murph, J. Hannig, and J. Williams.
MATH-512 Optimization on Manifolds Spring 2023 Project 1: Gaussian Mixture Models
Regression Graph Neural Network (regGNN) for cognitive score prediction.
Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation
Optimised Orientation Tracking using Riemann Stochastic Gradient Descent (RSGD)
Sensitivity Analysis of Deep Neural Networks (AAAI-19 paper)
Riemannian stochastic optimization algorithms: Version 1.0.3
Subsampled Riemannian trust-region (RTR) algorithms
Measure the distance between two spectra/signals using optimal transport and related metrics
C++ library for meshes and finite elements on manifolds
Project in Advanced Robotics course project at SDU 21/22. Implementation of learning method for skills for arm robots based on GMM with Rieamannian Manifolds
Notes prepared for seminars, compiled from books, or taken in classes are included in this repository. There might be some notes prepared by other seminar participants, which are labelled accordingly.
The code for vector transport free LBFGS quasi-Newton's optimization on the Riemannian manifolds
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