PPT-Principles of Dynamic Causal Modelling

Author : tawny-fly | Published Date : 2018-01-31

DCM Charité University Medicine Berlin Department of Neurology University College London Wellcome Trust Centre for Neuroimaging Bernadette van Wijk SPM course

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Principles of Dynamic Causal Modelling: Transcript


DCM Charité University Medicine Berlin Department of Neurology University College London Wellcome Trust Centre for Neuroimaging Bernadette van Wijk SPM course for MEG amp EEG . Jean-Philippe Pellet. Andre . Ellisseeff. Presented by Na Dai. Motivation. Why structure . l. earning?. What are Markov blankets?. Relationship between feature selection and Markov blankets?. Previous work. Ognyan. Oreshkov. , . Fabio . Costa. , . ČaslavBrukner. Bhubaneswar. arXiv:1105.4464. 20 December2011. Conference on Quantum Information. X. T. D. E. A. B. C. A. B. C. D. E. Measurements in space-time. Does Bell’s theorem prevent the use of causal explanations in quantum mechanics?. Part I:. Locality, Bell’s version of locality, and its discontents. The greatest mystery in science?. Locality. = “things do not go faster than . Abstract. In many real-world applications, it is important to mine causal relationships where an event or event pattern causes certain outcomes with low probability. Discovering this kind of causal relationships can help us prevent or correct negative outcomes caused by their antecedents. In this paper, we propose an innovative data mining framework and apply it to mine potential causal associations in electronic patient data sets where the drug-related events of interest occur infrequently. Specifically, we created a novel interestingness measure, exclusive causal-leverage, based on a computational, fuzzy recognition-primed decision (RPD) model that we previously developed. On the basis of this new measure, a data mining algorithm was developed to mine the causal relationship between drugs and their associated adverse drug reactions (ADRs). . from . Mass Cytometry Data. Presenters: . Ioannis Tsamardinos. and Sofia Triantafillou. Institute of Computer Science, Foundation for Research and Technology, Hellas. Computer Science Department, University of Crete. Michael Rosenblum. March 16, 2010. Overview. I describe the set of assumptions encoded by a causal directed acyclic graph (DAG). I use an example from page 15 of the book . Causality. by Judea Pearl (2009). . : A Ground-Breaking use of Directed Acyclic Graphs. Bob Stoddard SEMA. Mike Konrad. SEMA. Copyright 2015 Carnegie Mellon University. This . material is based upon work funded and supported by the Department of Defense under Contract No. FA8721-05-C-0003 with Carnegie Mellon University for the operation of the Software Engineering Institute, a federally funded research and development center.. Susan Athey, Stanford GSB. Based on joint work with Guido Imbens, Stefan Wager. References outside CS literature. Imbens and Rubin Causal Inference book (2015): synthesis of literature prior to big data/ML. Faculty of Physics, University of Vienna &. Institute . for Quantum Optics . and Quantum Information, Vienna . Mateus . Araujo. , . Cyril . Branciard, Fabio Costa, Adrian Feix. , Christina . Giarmatzi, Ognyan Oreshkov, Magdalena Zych. PcOR. : . controversies in the field. Heejung Bang, PhD. UC-Davis. 1. Why PCOR?. Me as . a . negative/null/lazy researcher-patient. . & co-I of a PCORI trial, my personal and honest feelings about . Naftali Weinberger. Tilburg Center for Logic, Ethics and Philosophy of Science. Time and Causality in the Sciences. June 8. th. , 2017. Principle of the . C. ommon Cause. iPad. Happiness. iPad. Happiness. Causes are . difference-makers. .. Effect need not be . universal/deterministic. .. N. ot . everyone who is bitten by a cobra . dies. .. N. ot . everyone who dies is bitten by a . cobra. .. B. ut . cobra bites still cause . Presented by: Arvind Kouta. 1. Consistency Models. Strict Consistency: operations are executed in order of wall-clock time (NTP). Sequential Consistency: operations are executed in some global ordering (Total Ordering). : A Mechanist Perspective. Stuart Glennan. Butler . University. The singularist and generalist view of causation. The. generalist view: Particular events are causally related because they fall under general laws.

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