cornellius-gp / linear_operatorLinks
A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
☆112Updated 5 months ago
Alternatives and similar repositories for linear_operator
Users that are interested in linear_operator are comparing it to the libraries listed below
Sorting:
- Matrix-free linear algebra in JAX.☆135Updated last week
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆130Updated 11 months ago
- Gaussian processes in JAX and Flax.☆526Updated last week
- Turning SymPy expressions into PyTorch modules.☆148Updated 2 years ago
- Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX☆207Updated 2 weeks ago
- Mathematical operations for JAX pytrees☆200Updated 8 months ago
- Large-scale, multi-GPU capable, kernel solver☆190Updated last month
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆462Updated last week
- Tutorial materials of the Probabilistic Numerics Spring School.☆35Updated 2 years ago
- Minimal Implementation of Bayesian Optimization in JAX☆95Updated 4 months ago
- ☆180Updated last week
- Multiple dispatch over abstract array types in JAX.☆128Updated 2 months ago
- Turn SymPy expressions into trainable JAX expressions.☆347Updated 4 months ago
- Riemannian Optimization Using JAX☆52Updated last year
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆50Updated 4 months ago
- Second Order Optimization and Curvature Estimation with K-FAC in JAX.☆282Updated last month
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆235Updated last year
- Normalizing Flows using JAX☆84Updated last year
- A generic interface for linear algebra backends☆73Updated 5 months ago
- Oryx is a library for probabilistic programming and deep learning built on top of Jax.☆275Updated this week
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆282Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Zonal Spherical Harmonics in d Dimensions in TensorFlow, PyTorch and Jax☆33Updated last year
- Stencil computations in JAX☆71Updated last year
- Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax☆464Updated last month
- Minimal JAX implementation of k-nearest neighbors using a k-d tree.☆47Updated last month
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 10 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Bayesian inference with Python and Jax.☆34Updated 2 years ago