Efficient global optimization toolbox in Rust: bayesian optimization, mixture of gaussian processes, sampling methods
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Updated
Jun 3, 2024 - Rust
Efficient global optimization toolbox in Rust: bayesian optimization, mixture of gaussian processes, sampling methods
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Surrogate Modeling Toolbox
NKCS model for exploring aspects of (surrogate-assisted) coevolution.
EA codes from CIAM Group at SUSTech, Shenzhen, China
Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness in Fennoscandia with Confidence
Surrogate modeling and optimization for scientific machine learning (SciML)
This repository contains code and data for optimizing punch and die design to minimize punched deviations in PCB registraion.
Package for data-driven and phenomenological gravitational waveform models
DrivAerNet: A Parametric Car Dataset for Data-driven Aerodynamic Design and Graph-Based Drag Prediction
A GNN-based surrogate model of urban drainage networks.
Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network
An easy to use interface to gravitational wave surrogate models
Sandia Uncertainty Quantification Toolkit
core C++ library
Dimension reduced surrogate construction for parametric PDE maps
Source code for Generative Adversarial Bayesian Optimization (GABO) for Surrogate Objectives
Python package 'dgpsi' for deep and linked Gaussian process emulations
A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays
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