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» Akaike causality in state space
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BC
2007
113views more  BC 2007»
13 years 4 months ago
Akaike causality in state space
We present a new approach of explaining partial causality in multivariate fMRI time series by a state space model. A given single time series can be divided into two noise-driven ...
Kin Foon Kevin Wong, Tohru Ozaki
JMLR
2011
175views more  JMLR 2011»
12 years 11 months ago
Causal Time Series Analysis of Functional Magnetic Resonance Imaging Data
This review focuses on dynamic causal analysis of functional magnetic resonance (fMRI) data to infer brain connectivity from a time series analysis and dynamical systems perspecti...
Alard Roebroeck, Anil K. Seth, Pedro A. Valdes-Sos...
AAAI
2008
13 years 7 months ago
Limits and Possibilities of BDDs in State Space Search
This paper investigates the impact of symbolic search for solving domain-independent action planning problems with binary decision diagrams (BDDs). Polynomial upper and exponential...
Stefan Edelkamp, Peter Kissmann
IJUFKS
2000
111views more  IJUFKS 2000»
13 years 4 months ago
A Factorized Representation of Independence of Causal Influence and Lazy Propagation
Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
Anders L. Madsen, Bruce D'Ambrosio
SAS
2009
Springer
212views Formal Methods» more  SAS 2009»
14 years 5 months ago
The Causal Graph Revisited for Directed Model Checking
Directed model checking is a well-established technique to tackle the state explosion problem when the aim is to find error states in large systems. In this approach, the state spa...
Martin Wehrle, Malte Helmert