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MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data
(Journal article; Peer reviewed, 2024)We introduce MCCE: Monte Carlo sampling of valid and realistic Counterfactual Explanations for tabular data, a novel counterfactual explanation method that generates on-manifold, actionable and valid counterfactuals by ... -
Statistical Embedding: Beyond Principal Components
(Journal article; Peer reviewed, 2023)There has been an intense recent activity in embedding of very high-dimensional and nonlinear data structures, much of it in the data science and machine learning literature. We survey this activity in four parts. In the ... -
Some recent trends in embeddings of time series and dynamic networks
(Journal article; Peer reviewed, 2023)We give a review of some recent developments in embeddings of time series and dynamic networks. We start out with traditional principal components and then look at extensions to dynamic factor models for time series. Unlike ... -
A new framework for semi-Markovian parametric multi-state models with interval censoring
(Journal article; Peer reviewed, 2023)There are few computational and methodological tools available for the analysis of general multi-state models with interval censoring. Here, we propose a general framework for parametric inference with interval censored ... -
A comparative study of methods for estimating model-agnostic Shapley value explanations
(Journal article; Peer reviewed, 2024)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 learning models in the industry and academia. ...
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