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cs.LG2026
Conveyance: A Versatile Framework for Learning in Structured Class Spaces
Yasser Taha, Grégoire Montavon, Nils Körber
While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-agnostic in many real-world ap…
cs.LG2026
Evaluating quality in synthetic data generation for large tabular health datasets
Jean-Baptiste Escudié, Benjamin Barnes, Stefan Meisegeier +3
There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historical epidemiological data. Thi…