goroda / GPEXP
Experimental Design for Gaussian Process Regression in Python
☆12Updated 3 years ago
Alternatives and similar repositories for GPEXP:
Users that are interested in GPEXP are comparing it to the libraries listed below
- Simulation-Enabled Prediction, Inference, and Analysis: physics-informed statistical learning.☆35Updated last year
- Differentiable interface to FEniCS for PyMC3☆20Updated 2 years ago
- Differentiable interface to FEniCS for JAX☆53Updated 3 years ago
- Examples in PyAMG☆25Updated 6 months ago
- AlgoPy is a Research Prototype for Algorithmic Differentation in Python☆83Updated 9 months ago
- An implementation of the 1. Parallel, 2. Streaming, 3. Randomized SVD using MPI4Py☆59Updated 3 years ago
- Dynamic Mode Decomposition☆59Updated 7 years ago
- Kernel methods for statistical modeling of dynamical systems☆24Updated 3 months ago
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆93Updated last year
- ☆31Updated 2 years ago
- Sequential Monte Carlo working on top of pymc☆50Updated 6 years ago
- ☆99Updated last year
- PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential op…☆26Updated last year
- Bibtex for various Python science and machine learning software☆32Updated 2 years ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆125Updated 6 months ago
- A library for high-level algorithmic differentiation☆18Updated 2 weeks ago
- Bayesian Dynamic Mode Decomposition (Bayesian DMD)☆18Updated 3 years ago
- PyRSB: a Python interface to the librsb Sparse Matrix library☆19Updated 3 years ago
- PyTorch implemetation of multi-layer quasi-geostrophic model on rectangular domain with solid boundaries.☆10Updated 2 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆32Updated last year
- Numerical differentiation with regularization, allowing differentiation of noisy data without amplifying noise. Uses total variation and …☆30Updated 6 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆67Updated 4 years ago
- Second Order ERror Propagation☆46Updated 6 years ago
- SciPy fixes and extensions☆19Updated 3 years ago
- Gaussian processes with spherical harmonic features in JAX☆14Updated last year
- Educational materials to learn how to employ Bayesian optimization techniques for parameter estimation of computational and statistical m…☆14Updated last year
- A Python library for training neural ODEs.☆21Updated 2 months ago
- This Python package aims at providing tools to study stochastic processes: integrate SDEs, solve Fokker-Planck equations, sample rare eve…☆11Updated 4 years ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆25Updated 3 years ago