Surrogate Modeling Toolbox

🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.

A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks

Surrogate modeling and optimization for scientific machine learning (SciML)

Surrogate Optimization Toolbox for Python

Applications of PINOs

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

Encoding physics to learn reaction-diffusion processes

Sandia Uncertainty Quantification Toolkit

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

3D CNN to predict single-phase flow velocity fields

A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays

linear and non-linear solvers, time integration, roms

Multi-fidelity Generative Deep Learning Turbulent Flows

Dimension reduced surrogate construction for parametric PDE maps

Efficient Multiscale Topology Optimization

A step-by-step guide for surrogate optimization using Gaussian Process surrogate model

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

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

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. :/