Riemannian Adaptive Optimization Methods with pytorch optim
-
Updated
May 9, 2026 - Python
Riemannian Adaptive Optimization Methods with pytorch optim
A C++ library of Markov Chain Monte Carlo (MCMC) methods
Regression Graph Neural Network (regGNN) for cognitive score prediction.
Implementation of Deep SPDNet in pytorch
Riemannian stochastic optimization algorithms: Version 1.0.3
Measure the distance between two spectra/signals using optimal transport and related metrics
[PNAS 2025] Code of "Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design".
Official implementation of the NeurIPS 25 paper of Riemannian Consistency Model (RCM) for few-step generation on Riemannian manifolds.
Riemannian metrics to measure distances in latent space of VAEs
Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation
SAC-N-GMM: Robot Skill Refining and Sequencing for Long-Horizon Manipulation Tasks
Sensitivity Analysis of Deep Neural Networks (AAAI-19 paper)
C++ library for meshes and finite elements on manifolds
Subsampled Riemannian trust-region (RTR) algorithms
Official repository for Cholesky Space for Brain-Computer Interfaces.
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
Python library for differential geometry, providing numerical tools for intrinsic geometric computations and PDE solving on manifolds.
[NeurIPS 2025] The official implementation of "Geometric Imbalance in Semi-Supervised Node Classification".
A package providing tractable examples of parallel transport for several matrix manifolds
Add a description, image, and links to the riemannian-manifold topic page so that developers can more easily learn about it.
To associate your repository with the riemannian-manifold topic, visit your repo's landing page and select "manage topics."