Riemannian Adaptive Optimization Methods with pytorch optim
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Updated
Jan 27, 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
Sensitivity Analysis of Deep Neural Networks (AAAI-19 paper)
SAC-N-GMM: Robot Skill Refining and Sequencing for Long-Horizon Manipulation Tasks
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
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