philipphennig / NumericsOfMLView external linksLinks
Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen
☆226Mar 29, 2024Updated last year
Alternatives and similar repositories for NumericsOfML
Users that are interested in NumericsOfML are comparing it to the libraries listed below
Sorting:
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆200Sep 18, 2023Updated 2 years ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Jul 20, 2024Updated last year
- Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing☆131Feb 3, 2026Updated last week
- 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
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆43Apr 12, 2023Updated 2 years ago
- Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…☆11May 8, 2023Updated 2 years ago
- Probabilistic Numerics in Python.☆458Jul 3, 2025Updated 7 months ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆35May 10, 2023Updated 2 years ago
- ☆35Dec 15, 2025Updated last month
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆33Apr 26, 2024Updated last year
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Feb 25, 2023Updated 2 years ago
- A zoo of implementations of differential equation problems in NumPy and JAX. Oscillators, chemical reactions, n-body problems, epidemiolo…☆17Dec 28, 2023Updated 2 years ago
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Jul 19, 2023Updated 2 years ago
- Laplace approximations in JAX.☆43Feb 6, 2026Updated last week
- Sketched linear operations for PyTorch☆100Oct 24, 2025Updated 3 months ago
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Feb 8, 2025Updated last year
- Probabilistic Finite Volume Method based on Affine Gaussian Process inference☆11Jun 10, 2024Updated last year
- Repo for materials for coordinating work on improving Julia's function documentation☆10Jul 30, 2022Updated 3 years ago
- Marginal distributions and Markov kernels that play nice with each other for the purpose of Bayesian state estimation.☆18Oct 22, 2025Updated 3 months ago
- Repository for the course Probabilistic Machine Learning at Tübingen University☆26May 17, 2020Updated 5 years ago
- Physics-Enhanced Regression for Initial Value Problems☆20Feb 7, 2024Updated 2 years ago
- A package for computing matrix exponentials and finite horizon Gramians☆11Jan 21, 2026Updated 3 weeks ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆53Updated this week
- Figure sizes, font sizes, fonts, and more configurations at minimal overhead. Fix your journal papers, conference proceedings, and other …☆727Jan 29, 2026Updated 2 weeks ago
- A light-weight library to help you create better plots for scientific publications, by taking care of the annoying bits like figure size,…☆52Jun 12, 2025Updated 8 months ago
- Julia package for various special functions based on `log` and `exp`.☆83Jan 1, 2026Updated last month
- Course material for the PhD course in Advanced Bayesian Learning☆61Mar 1, 2025Updated 11 months ago
- ☆12Jun 24, 2021Updated 4 years ago
- Interface designs for enforcing static computations in array functions with Julia☆15Updated this week
- Port of Statistical Rethinking (2nd edition) code to Julia☆136May 22, 2022Updated 3 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Dec 22, 2023Updated 2 years ago
- Integrating Neural Ordinary Differential Equations, the Method of Lines, and Graph Neural Networks☆18Oct 29, 2023Updated 2 years ago
- A common framework for implementing and using log densities for inference.☆45Oct 13, 2025Updated 4 months ago
- Research package for automatic differentiation of programs containing discrete randomness.☆217Mar 27, 2025Updated 10 months ago
- Laplace approximations for Deep Learning.☆534Apr 22, 2025Updated 9 months ago
- Fast matrix multiplication and division for Toeplitz matrices in Julia☆73Dec 16, 2025Updated last month
- ☆18Jun 23, 2023Updated 2 years ago
- The official implementation of Non-separable Spatio-temporal Graph Kernels via SPDEs.☆16Jun 2, 2022Updated 3 years ago
- ☆19Dec 22, 2025Updated last month