Predicting movable bridge deck expansion: A machine learning and asset management perspective

Automation of the clipping process in cryogenic electron tomography

AI Model Lifecycle Management: Systematic Mapping Study and Solution for AI Democratisation

Machine Learning for Software Refactoring: a Large-Scale Empirical Study

Ionic Force Field Parameterization with Bayesian Optimization

Novel machine learning methods to enhance wind power probabilistic forecasting: SPinHy-NN framework proposal for European electricity markets

A machine learning assessment of multi-resolution remote sensing data for Natura 2000 dune habitat classification

Design of a Graph Neural Network: to predict the optimal resolution of the Sonar Performance Model

Atrial Fibrillation classification from a short single lead ECG recording

A systematic approach to deal with highly imbalanced data when predicting flight cancellations and delays

Data driven turbulence modelling

Early Warning model for Thunderstorms around Lake Victoria

Effective Primary Healthcare Differential Diagnosis: A Machine Learning Approach

Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems

Enhancement of data-driven turbulence models for wind turbine wake applications

Investigating Physics-Informed Neural Networks for solving PDEs

Extracting geomechanical information from borehole microseismic data with machine learning

Unsatisfiable core learning for Chuffed: Improving the performance of Chuffed, a Lazy-Clause-Generation solver, by using machine learning to predict unsatisfiable cores

Learning Efficient Search Approximation in Mixed Integer Branch and Bound

Applying Machine Learning to Learn System Dynamics Models for Urban Systems