EEA-sensors / sqrt-parallel-smoothers
A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algorithms, both in a sequential and parallel fashion, as well as efficient gradient rules for computing gradients of required quantities (such as the pseudo-loglikelihood of the system).
☆12Updated last week
Related projects ⓘ
Alternatives and complementary repositories for sqrt-parallel-smoothers
- ☆10Updated 2 years ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆20Updated 4 months ago
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆11Updated 3 weeks ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆34Updated 3 weeks ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- A generic interface for linear algebra backends☆70Updated 4 months ago
- Exponential families for JAX☆55Updated this week
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆38Updated last year
- ☆36Updated 3 years ago
- A light interface to serial and multi-threaded Sequential Monte Carlo☆31Updated 2 years ago
- GPFlow based implementation of temporal parallellization of state space GPs☆15Updated 2 years ago
- A zoo of implementations of differential equation problems in NumPy and JAX. Oscillators, chemical reactions, n-body problems, epidemiolo…☆13Updated 10 months ago
- ☆13Updated 3 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆95Updated last year
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆21Updated 6 months ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆96Updated last year
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Codes for Hilbert space reduced-rank GP regression☆13Updated 5 years ago
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆25Updated 3 months ago
- A simple library to run variational inference on Stan models.☆27Updated last year
- A framework for composing Neural Processes in Julia☆76Updated 3 years ago
- Gradient-informed particle MCMC methods☆11Updated 9 months ago
- Gaussian Markov Random Fields (GMRFs) and Integrated Nested Laplace Approximation (INLA)☆19Updated 7 months ago
- Combination of transformers and diffusion models for flexible all-in-one simulation-based inference☆44Updated 5 months ago
- Conditional density estimation with neural networks☆27Updated 3 months ago
- Gaussian Processes for Sequential Data☆18Updated 3 years ago
- A flexible toolkit for simulation based inference in Julia☆18Updated last week
- Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo i…☆101Updated 2 years ago