Surrogate Modeling Toolbox
-
Updated
Jun 7, 2024 - Jupyter Notebook
Surrogate Modeling Toolbox
Surrogate modeling and optimization for scientific machine learning (SciML)
Surrogate Optimization Toolbox for Python
3D CNN to predict single-phase flow velocity fields
Sandia Uncertainty Quantification Toolkit
Applications of PINOs
An easy to use interface to gravitational wave surrogate models
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Encoding physics to learn reaction-diffusion processes
DrivAerNet: A Parametric Car Dataset for Data-driven Aerodynamic Design and Graph-Based Drag Prediction
Multi-fidelity Generative Deep Learning Turbulent Flows
A step-by-step guide for surrogate optimization using Gaussian Process surrogate model
Python package 'dgpsi' for deep and linked Gaussian process emulations
core C++ library
A python package for surrogate models that interface with calibration and other tools
Surrogate model library for Derivative-Free Optimization
LE-PDE accelerates PDEs' forward simulation and inverse optimization via latent global evolution, achieving significant speedup with SOTA accuracy
In this repository I publish the python code, that was part of my master thesis. The thesis can be found here, however its in German though, sry. :/
Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
A GNN-based surrogate model of urban drainage networks.
Add a description, image, and links to the surrogate-models topic page so that developers can more easily learn about it.
To associate your repository with the surrogate-models topic, visit your repo's landing page and select "manage topics."