22 citations · 68 across the 9 of their papers we have counts for
5 papers · 1 filter
Optimal transport for causal discovery
Ruibo Tu, Kun Zhang, Hedvig Kjellström +1
To determine causal relationships between two variables, approaches based on Functional Causal Models (FCMs) have been proposed by properly restricting model classes; however, the…
Causal Discovery from Conditionally Stationary Time Series
Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra +4
Causal discovery, i.e., inferring underlying causal relationships from observational data, is highly challenging for AI systems. In a time series modeling context, traditional caus…
How Do Fair Decisions Fare in Long-term Qualification?
Xueru Zhang, Ruibo Tu, Yang Liu +4
Although many fairness criteria have been proposed for decision making, their long-term impact on the well-being of a population remains unclear. In this work, we study the dynamic…
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
Ruibo Tu, Kun Zhang, Bo Christer Bertilson +2
Discovery of causal relations from observational data is essential for many disciplines of science and real-world applications. However, unlike other machine learning algorithms, w…
Causal Discovery in the Presence of Missing Data
Ruibo Tu, Kun Zhang, Paul Ackermann +4
Missing data are ubiquitous in many domains including healthcare. When these data entries are not missing completely at random, the (conditional) independence relations in the obse…