master / tensorflow-riemopt
A library for optimization on Riemannian manifolds
☆102Updated last year
Related projects ⓘ
Alternatives and complementary repositories for tensorflow-riemopt
- Riemannian Convex Potential Maps☆68Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆115Updated last year
- Deep Neural Networks Entropy from Replicas☆32Updated 5 years ago
- Examples of more involved applications using Geomstats☆32Updated 3 years ago
- ☆98Updated 3 years ago
- ☆36Updated 4 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆42Updated 3 years ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆107Updated this week
- A manifold optimization library for deep learning☆236Updated 3 years ago
- ☆18Updated last year
- Algorithms for computations on random manifolds made easier☆85Updated 11 months ago
- Riemannian Optimization Using JAX☆45Updated last year
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆52Updated 2 years ago
- Differentiable and numerically stable implementation of the matrix exponential☆32Updated 4 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆54Updated 5 years ago
- ☆22Updated 4 years ago
- Experiments for the AISTATS publication on Reparameterizing Distributions over Lie Groups☆52Updated 2 years ago
- Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)☆43Updated 3 years ago
- ☆258Updated last year
- Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.☆69Updated 3 months ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆35Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 3 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆53Updated 3 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch☆76Updated 5 months ago
- paper lists and information on mean-field theory of deep learning☆75Updated 5 years ago
- B-Spline CNNs on Lie groups☆53Updated 4 years ago