BACKGROUND Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this pape...

Learning Granger causality for general point processes is a very challenging task. In this paper, we propose an effective method, learning Granger causality, for a special but significant type of point processes — Hawkes process. According to the relationship between Hawkes process’s impact function and its Granger causality graph, our model represents impact functions using a series of basis f...

Causality has been an important concept in philosophy at least since the days of Aristotle and his "four causes" theory. Just for how long causality has been studied mathematically is uncertain due to the often blurred lines between mathematics and philosophy, but even today assigning causality (let alone culpability) to a pair of events requires some degree of human intuition. This paper will ...

Two key ideas of scientific explanation −explanation as causal information and explanation as unification– have frequently been set into mutual opposition. This paper proposes a “dialectical solution” to this conflict, by arguing that causal explanations are preferable to non-causal ones, because they lead to a higher degree of unification at the level of explaining statistical regularities. Th...

In the legal setting, "cause" is composed of at least two distinct components, of which only one is related to "causality" as scientists understand it. I argue that the alleged separation of the social issue of "scope of responsibility" from the objective question of scientific causality is illusory. "Scientific causality" also plays an essential social role in the legal setting.

Token causality refers to the causal relationship between system events on an individual system execution, as opposed to general causality, where relationships between types of events are studied. When a system fails at run-time, represented as the violations of certain system safety properties on an observed system execution trace, the investigation of token causality is helpful in understandi...

Hawking's stable causality implies Sorkin and Woolgar's K-causality. The work investigates the possible equivalence between the two causality requirements , an issue which was first considered by H. Seifert and then raised again by R. Low after the introduction of K-causality. First, a new proof is given that a spacetime is stably causal iff the Seifert causal relation is a partial order. It is...

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kern...