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cs.LG2026
Counterfactual Methods for Detecting Unfairness in Anti-Money Laundering Algorithms
Lea Multerer, Michele Inchingolo, David Kletz +3
The application of machine learning-based predictive algorithms to Anti-Money Laundering (AML) has grown rapidly, driven by the vast volume of financial transaction data available…
cs.LG2026
Learning Dynamical Systems from Multiple Sparse Datasets: A Hierarchical Bayesian Modeling Approach
Cristian Brugnara, Lea Multerer, Marco Forgione +1
Estimating parameters of dynamical systems from sparse, noisy, and irregularly sampled data is often severely ill-conditioned. When multiple related datasets are available, they pr…