grg: Computer Algebra System for Differential Geometry, Gravitation and Field Theory, automatically mirrored from https://reduce-algebra.sourceforge.io/grg32/grg32.php
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Updated
Jun 26, 2021
grg: Computer Algebra System for Differential Geometry, Gravitation and Field Theory, automatically mirrored from https://reduce-algebra.sourceforge.io/grg32/grg32.php
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.
Mirror of libmd on bitbucket: a molecular dynamics library optimized for soft matter
Comparing the performance of the DeepVO network under different loss functions
Alignment of Pangenome Graphs with Ricci Flow
Geometrical Layers for Pytorch Neural Networks
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.
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.
Repo for the paper 'Through-The-Wall Radar Imaging With Wall Clutter Removal Via Riemannian Optimization On The Fixed-Rank Manifold'
Maurer-Cartan-Lie frame connections ∇ Grassmann.jl TensorField derivations
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.
General relativity with automatic differentiation in Jax.
Learning-Rate-Free Stochastic Riemannian Optimization in JAX.
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.
Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399
Subsampled Riemannian trust-region (RTR) algorithms
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