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I'm very interested in modeling how people draw maps from memory. They use many kinds of information regarding distances between cities, angles along coastlines and borders, shapes and sizes of areas, etc, that somehow must come together coherently (and hopefully correctly). Since the piece of paper enforces coherence for free, it would be a waste of memory resources for humans to try to enforce...
Coherent Bayesian analysis of inspiral signals. (arXiv:0707.3962v1 [gr-qc])
We present in this paper a Bayesian parameter estimation method for the
analysis of interferometric gravitational wave observations of an inspiral of
binary compact objects using data recorded simultaneously by a network of
several interferometers at different sites. We consider neutron star or black
hole ...
Algebraic geometry of Gaussian Bayesian networks. [arXiv:0704.0918v1]
Authors: Seth Sullivant
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I'm now trying to show that ICA is totallyuseless for the Gaussian case. The idea being that ICA does not test for conditional independence. Apparently, Peter has been imagining otherwise, since in the Gaussian case, a regression coefficient being close to 0 implies conditional independence. I really pushed for my idea of Bayesianizing ICA, in order to deal with the more general case in which ...
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