22 citations · 28 across the 7 of their papers we have counts for
7 papers
FindMyText: Robust, Scalable Detection of Text Containment in Large Web-Crawled Corpora
Lars Henry Berge Olsen, Pierre Lison, Martin Jullum +1
We present FindMyText, an open-source Python package designed to efficiently assess whether a given text appears, in part or in full, within a text corpus. The tool builds on prior…
Computing Conditional Shapley Values Using Tabular Foundation Models
Lars Henry Berge Olsen, Dennis Christensen
Shapley values have become a cornerstone of explainable AI, but they are computationally expensive to use, especially when features are dependent. Evaluating them requires approxim…
shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python
Martin Jullum, Lars Henry Berge Olsen, Jon Lachmann +1
This paper introduces the shapr R package, a versatile tool for generating Shapley value-based prediction explanations for machine learning and statistical regression models. Moreo…
Improving the Weighting Strategy in KernelSHAP
Lars Henry Berge Olsen, Martin Jullum
In Explainable AI (XAI), Shapley values are a popular model-agnostic framework for explaining predictions made by complex machine learning models. The computation of Shapley values…
Precision of Individual Shapley Value Explanations
Lars Henry Berge Olsen
Shapley values are extensively used in explainable artificial intelligence (XAI) as a framework to explain predictions made by complex machine learning (ML) models. In this work, w…
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum +1
Shapley values originated in cooperative game theory but are extensively used today as a model-agnostic explanation framework to explain predictions made by complex machine learnin…
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum +1
Shapley values are today extensively used as a model-agnostic explanation framework to explain complex predictive machine learning models. Shapley values have desirable theoretical…