Surrogate Models Python Packages

egobox

Efficient global optimization toolbox in Rust: bayesian optimization, mixture of gaussian processes, sampling methods

smt

Surrogate Modeling Toolbox

apebench

[Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled Training; Rollout Metrics)

surmise

A python package for surrogate models that interface with calibration and other tools

tglfnn-ukaea

Neural network surrogate models of the TGLF quasilinear plasma turbulent transport simulator in various parameter spaces

pysot

Surrogate Optimization Toolbox for Python

teneva

Compact implementation of basic operations in the tensor-train (TT) format, including TT-SVD, TT-ALS, TT-ANOVA, TT-CROSS, TT-truncate for approximation of multidimensional arrays and multivariate functions

pyscipopt-ml

Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs

surfaces

Standardized test-functions for optimization algorithms and machine-learning

calisim

A toolbox for the calibration and evaluation of simulation models.

heron-model

Heron is a surrogate modelling toolkit for python, using Gaussian process regression.

surfaces-cec-data

Standardized test-functions for optimization algorithms and machine-learning

optilab

Simple framework for optimization functions and metamodels

insurance-distill

GBM-to-GLM distillation for insurance pricing - surrogate factor tables for Radar/Emblem rating engines

dgpsi

Deep and Linked Gaussian Process Emulations using Stochastic Imputation

surfaces-onnx-files

Standardized test-functions for optimization algorithms and machine-learning

statlml

Statistical Learning Models Library

neuroxai

[ESWA] NeuroXAI: Adaptive, Robust, Explainable Surrogate Framework for Determination of Channel Importance in EEG Application

uqtopus

UQTOPUS (Uncertainty Quantification Toolbox for OpenFOAM and Python Unified Simulation)

surfaces-dashboard

Standardized test-functions for optimization algorithms and machine-learning

statescale

A Python package for snapshot-driven upscaling of high-dimensional simulation states along arbitrary parameter or signal paths.

gradient-free-objective-functions

Standardized test-functions for optimization algorithms and machine-learning

pytuq

Python-only set of tools for uncertainty quantification.