Particle filtering and sequential parameter inference in Python
☆83Apr 22, 2023Updated 3 years ago
Alternatives and similar repositories for pyfilter
Users that are interested in pyfilter are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Basic Python particle filter☆181Apr 3, 2023Updated 3 years ago
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Feb 8, 2025Updated last year
- Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Sch…☆13Nov 7, 2022Updated 3 years ago
- A package for computing matrix exponentials and finite horizon Gramians☆11Jan 21, 2026Updated 4 months ago
- Collected code and materials from the intensive course preparing for the workshop on Sequential Monte Carlo (SMC) methods at Uppsala Univ…☆22Sep 24, 2018Updated 7 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Python module for uncertainty quantification using a parallel sequential Monte Carlo sampler☆134Updated this week
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆16Jul 9, 2018Updated 7 years ago
- ☆11Jul 6, 2023Updated 2 years ago
- Bayesian filters in PyTorch☆167May 25, 2023Updated 3 years ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆64Apr 17, 2024Updated 2 years ago
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆14Apr 20, 2026Updated last month
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Jul 19, 2023Updated 2 years ago
- Computation-Aware Kalman Filtering and RTS Smoothing☆19Mar 6, 2025Updated last year
- Probabilistic Finite Volume Method based on Affine Gaussian Process inference☆11Jun 10, 2024Updated 2 years ago
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- Full Bayesian Inference for Hidden Markov Models☆43Jan 14, 2019Updated 7 years ago
- GM-PHD filter implementation in python (Gaussian mixture probability hypothesis density filter)☆10Nov 14, 2016Updated 9 years ago
- Code examples for pyFTS☆51Oct 1, 2019Updated 6 years ago
- A comparison of PPL APIs☆27Jul 23, 2019Updated 6 years ago
- ☆12May 12, 2025Updated last year
- Sequential Monte Carlo working on top of pymc☆49Feb 21, 2019Updated 7 years ago
- Forecasting with PyTorch☆56Updated this week
- A unique time series library in Python that consists of Kalman filters (discrete, extended, and unscented), online ARIMA, and time differ…☆34Oct 23, 2017Updated 8 years ago
- Bayesian state-space modelling on high-performance hardware, including multicore, GPUs and distributed clusters.☆104Sep 12, 2023Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆13Oct 30, 2024Updated last year
- Source code and data for the paper "Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors"☆192Aug 17, 2023Updated 2 years ago
- ☆12May 7, 2015Updated 11 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆103Jul 6, 2023Updated 2 years ago
- Deep Reinforcement Learning applied to trading☆15Jan 29, 2019Updated 7 years ago
- Bayesian inference with state-space models using LibBi.☆25Apr 14, 2026Updated 2 months ago
- State space modeling with recurrent neural networks☆45Mar 30, 2018Updated 8 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆242Dec 22, 2023Updated 2 years ago
- Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature☆12Aug 10, 2021Updated 4 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Quadratic program minimizing risk while maintaining an expected return with the addition of rollover in the foreign exchange market☆12Nov 2, 2016Updated 9 years ago
- This code accompanies the manuscript "A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulati…