Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
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Updated
Jun 13, 2024 - Python
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
Riemannian Adaptive Optimization Methods with pytorch optim
A Python utility for analyzing a given solution to the Einstein's field equations. Built on Sympy.
Implementation of Deep SPDNet in pytorch
Algorithms for computations on random manifolds made easier
Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
A library for machine learning and quantum programming based on pyRiemann and Qiskit projects
Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399
Riemannian geometry in JAX
Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
riemanian brownian motion using jax
Learning-Rate-Free Stochastic Riemannian Optimization in JAX.
Geometrical Layers for Pytorch Neural Networks
Repo for the paper 'Through-The-Wall Radar Imaging With Wall Clutter Removal Via Riemannian Optimization On The Fixed-Rank Manifold'
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