AaltoML / SDELinks
Example codes for the book Applied Stochastic Differential Equations
☆205Updated 2 months ago
Alternatives and similar repositories for SDE
Users that are interested in SDE are comparing it to the libraries listed below
Sorting:
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆287Updated 4 years ago
- Manifold Markov chain Monte Carlo methods in Python☆236Updated last month
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆43Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆128Updated last year
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆189Updated 11 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆103Updated 2 years ago
- Sequential Neural Likelihood☆42Updated 6 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 5 years ago
- A Python library for mathematical optimization☆141Updated last year
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆96Updated 4 years ago
- ☆251Updated 3 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆35Updated 2 years ago
- Manifold-learning flows (ℳ-flows)☆233Updated 5 years ago
- Just a little MCMC☆235Updated last year
- Python and MATLAB code for Stein Variational sampling methods☆27Updated 6 years ago
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- Library for Deep Gaussian Processes based on GPflow☆18Updated 5 years ago
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Differentiable and numerically stable implementation of the matrix exponential☆33Updated 5 years ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆125Updated 2 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆122Updated 6 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆463Updated last year