spdes / chirpgp
Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes
☆11Updated 3 months ago
Alternatives and similar repositories for chirpgp:
Users that are interested in chirpgp are comparing it to the libraries listed below
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 2 months ago
- Gradient-informed particle MCMC methods☆11Updated last year
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆20Updated 7 months ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- GPFlow based implementation of temporal parallellization of state space GPs☆15Updated 2 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated last year
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆41Updated 3 months ago
- Practical tools for quantifying how well a sample approximates a target distribution☆27Updated 4 years ago
- Codes for Hilbert space reduced-rank GP regression☆14Updated 5 years ago
- Kernels, the machine learning ones☆14Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Conditional density estimation with neural networks☆30Updated last month
- ☆11Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆29Updated 7 months ago
- Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Sch…☆13Updated 2 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 8 months ago
- Probabilistic Finite Volume Method based on Affine Gaussian Process inference☆10Updated 8 months ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆62Updated last month
- All things Monte Carlo, written in JAX.☆30Updated last year
- A generic interface for linear algebra backends☆71Updated 7 months ago
- A framework for composing Neural Processes in Julia☆76Updated 3 years ago
- AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.☆39Updated last year
- ☆15Updated 3 years ago
- Self-tuning HMC algorithms and evaluations☆18Updated 4 months ago
- "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu☆27Updated 6 years ago
- Companion code in JAX for the paper Parallel Iterated Extended and Sigma-Point Kalman Smoothers.☆25Updated 6 months ago