Riemannian Adaptive Optimization Methods with pytorch optim
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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
Sensitivity Analysis of Deep Neural Networks (AAAI-19 paper)
SAC-N-GMM: Robot Skill Refining and Sequencing for Long-Horizon Manipulation Tasks
Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation
C++ library for meshes and finite elements on manifolds
Official repository for Cholesky Space for Brain-Computer Interfaces.
Subsampled Riemannian trust-region (RTR) algorithms
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
This repository provides the MATLAB implementation for the paper: Efficient Generative Modeling with Unitary Matrix Product States Using Riemannian Optimization
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".
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