Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
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Updated
May 30, 2024 - Python
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
A library for machine learning and quantum programming based on pyRiemann and Qiskit projects
Riemannian geometry in JAX
Computations and statistics on manifolds with geometric structures.
Comparing the performance of the DeepVO network under different loss functions
Geometrical Layers for Pytorch Neural Networks
Riemannian Adaptive Optimization Methods with pytorch optim
Repo for the paper 'Through-The-Wall Radar Imaging With Wall Clutter Removal Via Riemannian Optimization On The Fixed-Rank Manifold'
Algorithms for computations on random manifolds made easier
Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
This example compares the classification performance of linear support vector machine (LinearSVC) on the Riemannian Transfer Learning method (RPA, Rodrigues et al., 2018) and the golden-standard subject-wise train-test cross-validation method using real P300 BCI data.
Implementation of Deep SPDNet in pytorch
This repo is an implementation of the algorithm from the paper Distributed Consensus on Manifolds using the Riemannian Center of Mass. This algorithm synchronizes a set of agents over any manifold, as long as it has bounded sectional curvature. Any manifold in the Manopt library may be used.
This repo is an implementation of the algorithm from the paper Consensus on Lie groups for the Riemannian Center of Mass. This algorithm computes the Riemannian center of mass of a set of points in a distributed manner, generalizing the Euclidean average consensus dynamics.
Code implementations of the methods discussed in Generalized Fiducial Inference on Differentiable Manifolds by A. Murph, J. Hannig, and J. Williams.
A Julia package for manipulating data in the Riemannian manifold of positive definite matrices
A Python utility for analyzing a given solution to the Einstein's field equations. Built on Sympy.
Subsampled Riemannian trust-region (RTR) algorithms
General relativity with automatic differentiation in Jax.
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
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