Search Results for author: Elżbieta Sienkiewicz

Found 2 papers, 1 papers with code

Do not explain without context: addressing the blind spot of model explanations

no code implementations28 May 2021 Katarzyna Woźnica, Katarzyna Pękala, Hubert Baniecki, Wojciech Kretowicz, Elżbieta Sienkiewicz, Przemysław Biecek

The increasing number of regulations and expectations of predictive machine learning models, such as so called right to explanation, has led to a large number of methods promising greater interpretability.

BIG-bench Machine Learning Explainable Artificial Intelligence (XAI)

Deep spatial context: when attention-based models meet spatial regression

1 code implementation18 Jan 2024 Paulina Tomaszewska, Elżbieta Sienkiewicz, Mai P. Hoang, Przemysław Biecek

The DSCon allows for a quantitative measure of the spatial context's role using three Spatial Context Measures: $SCM_{features}$, $SCM_{targets}$, $SCM_{residuals}$ to distinguish whether the spatial context is observable within the features of neighboring regions, their target values (attention scores) or residuals, respectively.

regression

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