Computations and statistics on manifolds with geometric structures.

Riemannian Adaptive Optimization Methods with pytorch optim

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

A Python utility for analyzing a given solution to the Einstein's field equations. Built on Sympy.

Algorithms for computations on random manifolds made easier

Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399

IEEE Transactions on Emerging Topics in Computational Intelligence

Implementation of Deep SPDNet in pytorch

Riemannian Geometry workshop at vBCI Meeting 2021

Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper

A Julia package for manipulating data in the Riemannian manifold of positive definite matrices

A library for machine learning and quantum programming based on pyRiemann and Qiskit projects

A curated list of reading material and lecture notes for all things geometry. Mostly focussed on differential and Riemannian geometry with applications to physics, medical imaging and computer vision.

ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.

Riemannian geometry in JAX

Subsampled Riemannian trust-region (RTR) algorithms

Maurer-Cartan-Lie frame connections ∇ Grassmann.jl TensorField derivations

Comparing the performance of the DeepVO network under different loss functions

grg: Computer Algebra System for Differential Geometry, Gravitation and Field Theory, automatically mirrored from https://reduce-algebra.sourceforge.io/grg32/grg32.php

Learning-Rate-Free Stochastic Riemannian Optimization in JAX.