AaltoML / SDELinks
Example codes for the book Applied Stochastic Differential Equations
☆198Updated last week
Alternatives and similar repositories for SDE
Users that are interested in SDE are comparing it to the libraries listed below
Sorting:
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆240Updated last year
- A Python library for mathematical optimization☆141Updated last year
- Manifold Markov chain Monte Carlo methods in Python☆235Updated last week
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆284Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆188Updated 11 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Sequential Neural Likelihood☆42Updated 6 years ago
- Heterogeneous Multi-output Gaussian Processes☆53Updated 5 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆460Updated last year
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Just a little MCMC☆232Updated last year
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆409Updated last year
- Gaussian process modelling in Python☆224Updated 10 months ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- Manifold-learning flows (ℳ-flows)☆230Updated 4 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 9 years ago
- ☆250Updated 2 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆221Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB☆230Updated 2 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 4 years ago