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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24Cited by 0

ExactKAN ExplainBench: exact KAN explanations of public pretrained ReLU blocks

Rafael Asorey-Cacheda

Token-level activations, exact-equivalence reports, faithful local sensitivities and analytic straight-line Integrated Gradients obtained after algebraically converting a selected ReLU feed-forward block from a version-pinned public neural-network checkpoint into a piecewise-linear KAN. No fitting or retraining is used. The release includes the exact source snapshot needed for reproduction, but does not redistribute the upstream checkpoint or functionally equivalent KAN parameters. Contact: Rafael Asorey Cacheda, rafael.asorey@upct.es. Funding acknowledgement (AEI wording): Proyecto PID2023-148214OB-C21 financiado por MICIU/AEI/10.13039/501100011033 y por FEDER, UE. Project record: https://portalinvestigacion.upct.es/proyectos/921368/detalle

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Temporal Computation Audit for Spiking Neural Networks

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

Reproducibility Package for Explainable and Leakage-Conscious Machine Learning for Athlete Injury Risk Modeling Across Heterogeneous Datasets

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This reproducibility package supports the manuscript “Explainable and Leakage-Conscious Machine Learning for Athlete Injury Risk Modeling Across Heterogeneous Datasets.” It contains the executed and clean analysis notebooks, the corresponding Python script, exact software-version…

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