Sort by
Refine Your Search
-
horticultural data from digital images by analysing their content. The aim is to infer information that might not be immediately apparent, even to the photographer, in order to improve our understanding of animal
-
networks, Bayesian inference, computational neuroscience, mathematics.
-
on Artificial Intelligence and Statistics (AI+STATS 2001), pp253-260, Key West, Florida, U.S.A., Jan. 2001 P. J. Tan and D. L. Dowe (2003). MML Inference of Decision Graphs with Multi-Way Joins and Dynamic
-
: 04EX783), pp439-444 Frey and Osborne (2013) Frey and Osborne (2017) P. J. Tan and D. L. Dowe (2003). MML Inference of Decision Graphs with Multi-Way Joins and Dynamic Attributes , Proc. 16th Australian
-
. This will be achieved through frequency domain and time domain state and parameter estimation techniques to infer model states and parameters in real time to simultaneously track the anaesthetic brain states
-
learning is vulnerable to spurious correlations, novel causal discovery and inference methods will be developed to identify and reason over causal relationships among all associations from fused data. As the
-
back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum message length (MML) approach (Wallace and Boulton, 1968
-
Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
-
the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms
-
. Among the approaches used will be the Bayesian information-theoretic Minimum Message Length (MML) principle (Wallace and Boulton, 1968; Wallace and Dowe, 1999a; Wallace, 2005) References: Wallace, C.S