Surrogate Modeling Toolbox
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Updated
Jul 8, 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
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
An easy to use interface to gravitational wave surrogate models
Encoding physics to learn reaction-diffusion processes
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
Multi-fidelity Generative Deep Learning Turbulent Flows
core C++ library
A step-by-step guide for surrogate optimization using Gaussian Process surrogate model
Python package 'dgpsi' for deep and linked Gaussian process emulations
A python package for surrogate models that interface with calibration and other tools
LE-PDE accelerates PDEs' forward simulation and inverse optimization via latent global evolution, achieving significant speedup with SOTA accuracy
A GNN-based surrogate model of urban drainage networks.
Surrogate model library for Derivative-Free Optimization
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
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