12 citations · 17 across the 5 of their papers we have counts for
6 papers
Homophily and Incentive Effects in Use of Algorithms
Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta +2
As algorithmic tools increasingly aid experts in making consequential decisions, the need to understand the precise factors that mediate their influence has grown commensurately. I…
GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints
Mohammadsajad Abavisani, David Danks, Sergey Plis
Graphical structures estimated by causal learning algorithms from time series data can provide misleading causal information if the causal timescale of the generating process fails…
Dynamic Certification for Autonomous Systems
Georgios Bakirtzis, Steven Carr, David Danks +1
Autonomous systems are often deployed in complex sociotechnical environments, such as public roads, where they must behave safely and securely. Unlike many traditionally engineered…
Choosing with unknown causal information: Action-outcome probabilities for decision making can be grounded in causal models
Mauricio Gonzalez Soto, David Danks, Hugo J. Escalante Balderas +1
Decision-making under uncertainty and causal thinking are fundamental aspects of intelligent reasoning. Decision-making has been well studied when the available information is cons…
Causal Discovery from Subsampled Time Series Data by Constraint Optimization
Antti Hyttinen, Sergey Plis, Matti Järvisalo +2
This paper focuses on causal structure estimation from time series data in which measurements are obtained at a coarser timescale than the causal timescale of the underlying system…
Linearity Properties of Bayes Nets with Binary Variables
David Danks, Clark Glymour
It is "well known" that in linear models: (1) testable constraints on the marginal distribution of observed variables distinguish certain cases in which an unobserved cause jointly…