schmidtjonathan / probabilistic-ssmLinks
Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Schmidt, Krämer, Hennig)
☆13Updated 2 years ago
Alternatives and similar repositories for probabilistic-ssm
Users that are interested in probabilistic-ssm are comparing it to the libraries listed below
Sorting:
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Updated last year
- Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…☆11Updated 2 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated 2 years ago
- ☆38Updated 3 years ago
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 7 months ago
- Kernels, the machine learning ones☆14Updated 2 years ago
- DifferentialEquations.jl with PyTorch☆11Updated 2 years ago
- A flexible toolkit for simulation based inference in Julia☆19Updated last month
- Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing☆129Updated 2 months ago
- A zoo of implementations of differential equation problems in NumPy and JAX. Oscillators, chemical reactions, n-body problems, epidemiolo…☆15Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Repository for Deterministic Particle Flow Control framework☆10Updated 2 years ago
- This tutorial is a basic guide to understanding the Zig-Zag Sampling method. This document is released with the aim of diffusion and shar…☆21Updated 6 years ago
- Practical tools for quantifying how well a sample approximates a target distribution☆27Updated 4 years ago
- A generic interface for linear algebra backends☆73Updated 4 months ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆12Updated 8 months ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆30Updated last year
- Bayesian inference on spatial and spatiotemporal data, faster than you can say "Cholesky!"☆10Updated this week
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 5 months ago
- Implements Optimization and approximate uncertainty quantification algorithms, Ensemble Kalman Inversion, and Ensemble Kalman Processes.☆103Updated this week
- The official implementation of Non-separable Spatio-temporal Graph Kernels via SPDEs.☆16Updated 3 years ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆49Updated 3 months ago
- Density ratio estimation in Julia☆34Updated 7 months ago
- Dynamical systems modeling in Julia with 🐜 & 🐟☆35Updated 2 years ago
- A Julia framework for invertible neural networks☆165Updated 5 months ago
- Website for the book "The Elements of Differentiable Programming".☆13Updated 3 weeks ago