A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
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Updated
Sep 7, 2025 - Python
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays
Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
surrogate quantitative interpretability for deepnets
UQPyL is a python package for uncertainty quantification and parameter optimization. 参数不确定性分析及优化工具包。
A design optimization study of underwater vehicle using Bayesian optimization and deep learning based surrogate model
Surrogate model library for Derivative-Free Optimization
Design optimization of floating offshore wind turbine with surrogate models
Tutorials for the C++ pressio library
Reinforcement Learning Actors for Blade Pitch Control in Wind Turbine Systems
Heron is a surrogate modelling toolkit for python, using Gaussian process regression.
Blackbox provides a standarized and efficient interface for evaluating variety of blackbox functions for various surrogate-based design activities
A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives
Mitigating the high computational costs associated with applying Bayesian model updating in inverse problems / Uncertainty Quantification and Efficient Sensitivity Analysis by using Surrogate Models
Design of a surrogate-assisted (mu/mu,lambda)-ES
The official repository accompanying the paper "Deep Vision-Based Framework for Coastal Flood Prediction Under Climate Change Impacts and Shoreline Adaptations".
squid repository for manuscript analysis
This repository contains the packages that build the problem objects for the desdeo framework.
Multi-Criteria Decision Making (MCDM) Framework for Building Energy Systems with Expedited Computation using Machine Learning (ML) Techniques
Tools for constructing a surrogate model for a stochastic numerical model using Probabilistic Learning on Manifolds in a small data context
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