
Mavarick AI
Adversarial Robustness of Variational Autoencoders across Intersectional Subgroups.
Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study.
This tutorial series offers a hands-on guide to fairness-aware machine learning that targets beginners in Fair-ML.
Introduction to AI (2 hours) Data Acquisition (1.5 hours) Analysis, Visualization and AI Applications for Genetic Data (2 hours) AI Applications for Other Biotechnological Data (2 hours) Closure and Conclusions (0.5 hours)
An investigation into the fairness and bias implications of multimodal fusion techniques in AI-driven recruitment systems using the FairCVdb dataset, examining how different fusion strategies influence bias and impact fairness in hiring decisions.
EnvClus* is an unsupervised data-driven framework that forecasts the most probable realistic and smooth trajectory from a given query position of a vessel (entire route or underway forecasting) towards its destination port.