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Beyond Additive Decompositions: Interpretability Through Separability
arXiv:2605.31200v1 Announce Type: new Abstract: Interpretable machine learning requires models that are accurate and structurally faithful to the data. Existing explainability methods rely heavily on additive representations (e.g., Generalized Additive Models (GAMs), SHapley Additive exPlanations (SHAP), functional ANOVA), which can suffer from signal cancellation and off-support extrapolation in the presence of strong interactions. We propose Tensor Separation Learning (TSL), a regression...
Beyond Additive Decompositions: Interpretability Through Separability
Announce Type: replace Abstract: Interpretable machine learning requires models that are accurate and structurally faithful to the data. Existing explainability methods rely heavily on additive representations (e.g., Generalized Additive Models (GAMs), SHapley Additive exPlanations (SHAP), functional ANOVA), which can suffer from signal cancellation and off-support extrapolation in the presence of strong interactions. We propose Tensor Separation Learning (TSL), a regression model that...
Drone mimicking peregrine falcon gives hope to strawberry growers
Falcon-like drone drives birds away from strawberry crops in Qld trial Tue 2 Jun 2026 at 7:02am In short: Birds cause more than $300 million in Australian crop losses annually. A drone mimicking a peregrine falcon is being trialled to protect strawberries. The trial, funded by Hort Innovation, will run for three years.