This paper explores some issues having to do with the use of networks in scientific explanations. It focuses on the very common case in which what is of interest is the spread of some process (a disease, a neural signal etc.) along a network. In such cases, the use of a network in explanation requires the specification of a dynamics governing this process in addition to and independent of the network structure. Such a dynamics will incorporate causal information. This is one of several reasons why it is a mistake to think of network explanations, at least in typical applications, as entirely non-causal. In addition the independence of the network structure and the dynamics of the process occuring on it provides the key to the "directiona...
I examine the adequacy of the causal graph-structural equations approach to causation for modeling b...
Network theory is a branch of mathematics concerned with the analysis of the structure of graphs, t...
This thesis is a contribution to a deeper understanding of how information propagates and what this ...
Network explanations raise foundational questions about the nature of scientific explanation. The ch...
This paper considers the way mathematical and computational models are used in network neuroscience ...
Complex interacting networks are observed in systems from such diverse areas as physics, biology, ec...
Processes on networks consist of two interdependent parts: the network topology, consisting of the l...
Networks have become a general concept to model the structure of arbitrary relationships among entit...
In the last twenty years or so, since the publication of a seminal paper by Watts and Storgatz (1998...
In this article, network science is discussed from a methodological per- spective, and two central t...
Explanations in Bayesian networks are usually probabilistic measures of how well a hypothesis is sup...
In fact, much of the attraction of network theory initially stemmed from the fact that many networks...
Simple network models that focus only on graph topology or, at best, basic interactions are often in...
© Copyright © 2021 de Boer, de Bruin, Geurts and Glas.Borsboom and colleagues have recently proposed...
In the last couple of years, a few seemingly independent debates on scientific explanation have emer...
I examine the adequacy of the causal graph-structural equations approach to causation for modeling b...
Network theory is a branch of mathematics concerned with the analysis of the structure of graphs, t...
This thesis is a contribution to a deeper understanding of how information propagates and what this ...
Network explanations raise foundational questions about the nature of scientific explanation. The ch...
This paper considers the way mathematical and computational models are used in network neuroscience ...
Complex interacting networks are observed in systems from such diverse areas as physics, biology, ec...
Processes on networks consist of two interdependent parts: the network topology, consisting of the l...
Networks have become a general concept to model the structure of arbitrary relationships among entit...
In the last twenty years or so, since the publication of a seminal paper by Watts and Storgatz (1998...
In this article, network science is discussed from a methodological per- spective, and two central t...
Explanations in Bayesian networks are usually probabilistic measures of how well a hypothesis is sup...
In fact, much of the attraction of network theory initially stemmed from the fact that many networks...
Simple network models that focus only on graph topology or, at best, basic interactions are often in...
© Copyright © 2021 de Boer, de Bruin, Geurts and Glas.Borsboom and colleagues have recently proposed...
In the last couple of years, a few seemingly independent debates on scientific explanation have emer...
I examine the adequacy of the causal graph-structural equations approach to causation for modeling b...
Network theory is a branch of mathematics concerned with the analysis of the structure of graphs, t...
This thesis is a contribution to a deeper understanding of how information propagates and what this ...