andres-fr / skerch
Sketched matrix decompositions for PyTorch
☆67Updated 6 months ago
Related projects ⓘ
Alternatives and complementary repositories for skerch
- scipy linear operators for the Hessian, Fisher/GGN, and more in PyTorch☆18Updated 2 weeks ago
- Algorithms for computations on random manifolds made easier☆86Updated 11 months ago
- Riemannian Convex Potential Maps☆68Updated last year
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 3 years ago
- Agustinus' very opiniated publication-ready plotting library☆58Updated 2 months ago
- IVON optimizer for neural networks based on variational learning.☆53Updated 2 weeks ago
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆32Updated last year
- Riemannian Optimization Using JAX☆45Updated last year
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated last year
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Updated 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
- Parameter-Free Optimizers for Pytorch☆109Updated 6 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆94Updated 2 months ago
- Normalizing Flows using JAX☆82Updated 11 months ago
- Squared Non-monotonic Probabilistic Circuits☆19Updated 4 months ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated 7 months ago
- The Modified Differential Multiplier Method (MDMM) for PyTorch☆51Updated 3 years ago
- Convex potential flows☆78Updated 3 years ago
- [ICML 2024] SINGD: KFAC-like Structured Inverse-Free Natural Gradient Descent (http://arxiv.org/abs/2312.05705)☆20Updated 2 weeks ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆107Updated this week
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆95Updated last year
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- ASDL: Automatic Second-order Differentiation Library for PyTorch☆179Updated 3 months ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆89Updated 7 months ago
- Matrix-free linear algebra in JAX.☆106Updated 2 months ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆29Updated 2 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- Flow-matching algorithms in JAX☆77Updated 3 months ago
- Zonal Spherical Harmonics in d Dimensions in TensorFlow, PyTorch and Jax☆24Updated 6 months ago
- Differentiable and numerically stable implementation of the matrix exponential☆32Updated 4 years ago