General-purpose library for fitting models to data with correlated Gaussian-distributed noise
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Updated
Jul 16, 2024 - Python
General-purpose library for fitting models to data with correlated Gaussian-distributed noise
MITIM (MIT Integrated Modeling) Suite for Fusion Applications
A python package for parameter uncertainty quantification and optimization
NKCS model for exploring aspects of (surrogate-assisted) coevolution.
Python library for parallel multiobjective simulation optimization
MVRSM algorithm for optimising mixed-variable expensive cost functions.
A transformative approach to manufacturing optimization, focusing on the textile forming process. This research synergizes domain-specific knowledge with simulation modeling and introduces Bayesian optimization for efficient parameter space exploration.
Statistical learning models library for blackbox optimization
surF - a surrogate modeling method based on Discrete Fourier Transform
Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
This repository contains the packages that build the problem objects for the desdeo framework.
Source files of experiment resutls for the manusctipt that submitted to ESWA.
SKSurrogate is a suite of tools that implements surrogate optimization for expensive functions based on scikit-learn. The main purpose of SKSurrogate is to facilitate hyperparameter optimization for machine learning models and optimized pipeline design (AutoML).
Python platform for parallel Surrogate-Based Optimization
Code written for the BSc Project: Estimating Control Landscapes with Neural Networks by Susan Chen and Katie Xiao as part of our Imperial College London Physics degrees.
Self-Supervised Deep Learning based Surrogate Models for Fault-Tolerant Edge Computing
This is the official repository of the AI for TSP competition at IJCAI 2021
A Surrogate-Assisted Evolutionary Algorithm with Hypervolume Triggered Fidelity Adjustment for Noisy Multiobjective Integer Programming
This GOMORS algorithm is the modified version of what is uploaded in this repository: https://github.com/drkupi/GOMORS_pySOT.
Implementation of the PAMELI algorithm for computationally expensive multi-objective optimization
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