[PDF] Efficient Explanations from Empirical Explainers

Does Dataset Complexity Matters for Model Explainers?

RelEx: A Model-Agnostic Relational Model Explainer

30 mai 2020 Relational Models include Statistical relational learning (SRL) methods [1] ... There are mainly two groups of these iid model explainers.

Optimal Local Explainer Aggregation for Interpretable Prediction

Global explainers attempt to explain the full black box model across the entirety of the data. These models have a hard constraint to provide 100% coverage 

Explainer on SIP settlement model

What is the Single Instructing Party settlement model for instant payments? ----------. May 2021. With Riksbank joining the TARGET Instant Payment 

Training calibration-based counterfactual explainers for deep

counterfactual explainers for deep learning models in medical image analysis. Jayaraman J. Thiagarajan1? Kowshik Thopalli2

The Canna model: explainer. Assessing the impact of NHS Test and

13 sept. 2021 The Canna model: explainer. Assessing the impact of NHS Test and. Trace on COVID-19 transmission: June. 2020 to April 2021.

Analysis of Explainers of Black Box Deep Neural Networks for

27 nov. 2019 Abstract: Deep Learning is a state-of-the-art technique to make inference on extensive or complex data. As a black box model due to their ...

The Rùm Model Technical Annex - an explainer - GOV.UK

11 févr. 2021 The Rùm Model Technical Annex. - an explainer. Assessing the impact of test trace and isolate parameters on COVID-19 transmission in an ...

Efficient Explanations from Empirical Explainers

11 nov. 2021 expensive explainers. We train and test Em- pirical Explainers in the language domain and find that they model their expensive counter-.

PGM-Explainer: Probabilistic Graphical Model Explanations for

PGM-Explainer: Probabilistic Graphical Model. Explanations for Graph Neural Networks. Minh N. Vu. University of Florida. Gainesville FL 32611.