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

surrogate quantitative interpretability for deepnets

A python package for parameter uncertainty quantification and optimization

Mitigating the high computational costs associated with applying Bayesian model updating in inverse problems / Uncertainty Quantification and Efficient Sensitivity Analysis by using Surrogate Models

squid repository for manuscript analysis

This repository contains the packages that build the problem objects for the desdeo framework.

Learning Aerodynamics Through Data to Improve Optimization Algorithms

This repository contains scripts that were used for the experiments of our work named "Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling".

Surrogate modelling technique selectors

cNN-DP: Composite neural network with differential propagation for impulsive nonlinear dynamics.

Hierarchical generative and regressive machine learning for next generation materials screening

Statistical learning models library for blackbox optimization

A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives

DL models for generating stress fields in microstructures

cNN-DP: Composite neural network with differential propagation for impulsive nonlinear dynamics.