Package for data-driven and phenomenological gravitational waveform models

NKCS model for exploring aspects of (surrogate-assisted) coevolution.

Program that helps optimize our algorithm

Interpreting Categorical Data Classifiers using Explanation-based Locality

Surrogate Modelling package for OpenTURNS

This repository consist of a compendium of assignments and their respective solutions for an advanced course in Applied Bayesian Statistics

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

Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can! (Work presented at IEEE VIS 2021)

Quantum deep field for molecule

Machine Learning as an alternative to simulation models for decision making

Reinforcement Learning Actors for Blade Pitch Control in Wind Turbine Systems

Model identifiability pipeline using surrogate models trained on a latent space extracted by tensor decompositions.

R interface to 'dgpsi' for deep and linked Gaussian process emulations

AJCAI2023 workshop: Machine Learning for Data-driven Optimization

Uncertainty Quantification for Physical and Biological Models

Internal Jugular Vein oximeter project

MultiViewUNet: A Deep Learning Surrogate for Wall Shear Stress Prediction in Aortic Diseases

Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness in Fennoscandia with Confidence

Getting explanations for predictions made by black box models.

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.