Computations and statistics on manifolds with geometric structures.
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Updated
Sep 9, 2024 - Jupyter Notebook
Computations and statistics on manifolds with geometric structures.
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
IEEE Transactions on Emerging Topics in Computational Intelligence
Riemannian Geometry workshop at vBCI Meeting 2021
Algorithms for computations on random manifolds made easier
A library for machine learning and quantum programming based on pyRiemann and Qiskit projects
Subsampled Riemannian trust-region (RTR) algorithms
A Julia package for manipulating data in the Riemannian manifold of positive definite matrices
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.
Code implementations of the methods discussed in Generalized Fiducial Inference on Differentiable Manifolds by A. Murph, J. Hannig, and J. Williams.
riemanian brownian motion using jax
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.
Learning-Rate-Free Stochastic Riemannian Optimization in JAX.
Mirror of libmd on bitbucket: a molecular dynamics library optimized for soft matter
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