most citedWhen accurate prediction models yield harmful self-fulfilling prophecies

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cs.LG2026

Improving TabPFN's Synthetic Data Generation by Integrating Causal Structure

Davide Tugnoli, Andrea De Lorenzo, Marco Virgolin +1

Synthetic tabular data generation addresses data scarcity and privacy constraints in a variety of domains. Tabular Prior-Data Fitted Network (TabPFN), a recent foundation model for…

cs.LG2023

Unmasking the Chameleons: A Benchmark for Out-of-Distribution Detection in Medical Tabular Data

Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Ciná

Despite their success, Machine Learning (ML) models do not generalize effectively to data not originating from the training distribution. To reliably employ ML models in real-world…