SMT: The Surrogate Modeling Toolbox
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。
Collection of Multi-Fidelity benchmark functions
smt-optim: The Surrogate-Based Optimization software based on SMT
[NeurIPS 2022] Supervising the Multi-Fidelity Race of Hyperparameter Configurations
This repository comprises Jupyter Notebooks that serve as supplementary material to the journal article titled "Review of Multifidelity Models." The notebooks contain Python-based implementations that demonstrate toy problems in the multifidelity domain.
A set of reactor design benchmark problems to evaluate high-dimensional, expensive, and potentially multi-fidelity optimisation algorithms.
Project source code and data for multi-fidelity machine learning strategy for flame model identification
"Compute-optimal data scaling for neural surrogates via multi-fidelity training" @ NeurIPS 2026
A suite of codes for dynamic analysis of offshore slender structures
Spatiotemporal Gaussian process modeling for environmental data: non-stationary PDE prior, deep kernels, multi-fidelity fusion, and A-optimal sampling.非稳态 PDE + 核深度学习 + 多保真 Co-Kriging + 主动采样的物理约束克里金方法，用于复杂时空环境建模与预测
Flexible Gaussian Process model with user friendly kernel and mean function construction inspired by STHENO.
greedy nonlinear autoregression for multifidelity modeling
Multi-fidelity modeling of wind farm wakes based on a novel super-fidelity network
A minimal package for providing pretrained machine learning force fields (e.g. multi-fidelity M3GNet) for material simulations.
A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
Meta-Learning for Cross-Domain Multi-Fidelity Optimization | PhD Research Framework | Learning transferable fidelity allocation strategies across aerospace, robotics, materials, and fluids
Just a notebook reproducing the Non-linear Autoregressive Gaussian Process (Perdikaris et al, 2017) using Tensorflow Probability
To associate your repository with the multi-fidelity topic, visit your repo's landing page and select "manage topics."