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11/30/2021
Binary Independent Component Analysis via Non-stationarity
We consider independent component analysis of binary data. While fundame...
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09/30/2020
Towards Scalable Bayesian Learning of Causal DAGs
We give methods for Bayesian inference of directed acyclic graphs, DAGs,...
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09/21/2020
Identifying Causal Effects via Context-specific Independence Relations
Causal effect identification considers whether an interventional probabi...
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07/16/2020
Do-search – a tool for causal inference and study design with multiple data sources
Epidemiological evidence is based on multiple data sources including cli...
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02/04/2019
Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach
Causal effect identification considers whether an interventional probabi...
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02/25/2016
Causal Discovery from Subsampled Time Series Data by Constraint Optimization
This paper focuses on causal structure estimation from time series data ...
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09/26/2013
Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure
We present a very general approach to learning the structure of causal m...
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10/16/2012
Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables
Much of scientific data is collected as randomized experiments interveni...
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05/09/2012
Bayesian Discovery of Linear Acyclic Causal Models
Methods for automated discovery of causal relationships from non-interve...
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02/14/2012