Riemannian metrics to measure distances in latent space of VAEs
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Updated
Jan 7, 2019 - Python
Riemannian metrics to measure distances in latent space of VAEs
Implementing the algorithms of Kim et al. 2014 for regressing multiple symmetric positive definite matrices against real valued covariates.
Matlab implementation of paper "Principal Geodesic Analysis in the Space of Discrete Shells", SGP-2018
The code for vector transport free LBFGS quasi-Newton's optimization on the Riemannian manifolds
Notes prepared for seminars, compiled from books, or taken in classes are included in this repository. There might be some notes prepared by other seminar participants, which are labelled accordingly.
Project in Advanced Robotics course project at SDU 21/22. Implementation of learning method for skills for arm robots based on GMM with Rieamannian Manifolds
C++ library for meshes and finite elements on manifolds
Measure the distance between two spectra/signals using optimal transport and related metrics
Subsampled Riemannian trust-region (RTR) algorithms
Riemannian stochastic optimization algorithms: Version 1.0.3
Sensitivity Analysis of Deep Neural Networks (AAAI-19 paper)
Optimised Orientation Tracking using Riemann Stochastic Gradient Descent (RSGD)
Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation
Regression Graph Neural Network (regGNN) for cognitive score prediction.
MATH-512 Optimization on Manifolds Spring 2023 Project 1: Gaussian Mixture Models
Code implementations of the methods discussed in Generalized Fiducial Inference on Differentiable Manifolds by A. Murph, J. Hannig, and J. Williams.
Implementation of Deep SPDNet in pytorch
Algorithms for the approximation of an embedding for Markov chains.
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