Explainable Artificial Intelligence Techniques for the Analysis of Reinforcement Learning in Non-Linear Flight Regimes

Combining Type4Py’s Deep Similarity Learning-based Type Inference with Static Type Inference for Python

Analysing the Impact of Inline Comments for the Task of Code Captioning

Understanding Risk Extrapolation (REx) and when it finds Invariant Relationships

Surfacing Differences in Practices When Building Fair Machine Learning Systems with Fairness Toolkits: an Empirical Study

Empirical study of GANITE’s robustness to hidden confounders

Representation counts: the impact of embedding models on disease detection tasks from microbiome sequencing data

An empirical study of the effects of unconfoundedness on the performance of Propensity Score Matching

A Guidline for Creating Assessments in Machine Learning Education

Instructional Designs of Machine Learning: A research into the instructional designs used in introductory courses of machine learning in computer science bachelors

Explain Strange Learning Curves in Machine Learning

Detection and Classification of Faults in Residential PV Systems with a Synthetic PV Training Database: A Machine Learning-Based Approach Using the PVMD Toolbox to Generate Synthetic PV Yield Data

Sustainable and smart distribution networks: Machine Learning and Forecasting

User/Query-wise Metric Bounding in Learning to Rank

Guiding the specification of sociotechnical Machine Learning systems: Addressing vulnerabilities and challenges in Machine Learning practice

Supervised Classification of Aerosol Types from POLDER-3 and OMI satellite data: An investigative study into using microphysical parameters and class labels for aerosol classification

Digital Soil Mapping based on PDFs of Cone Penetration Tests and Vibro Cores using Image Processing and Machine Learning

Reduce model unfairness with maximal-correlation-based fairness optimization

Tender Price Predictor: Predicting Tender Prices of Dutch Infrastructure Projects with Machine Learning

Characterization and Mitigation of High-Confidence Errors Through the Use of Human-In-The-Loop Methods: Domain Expert Driven Approach to Model Development