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NIPS
2004
14 years 11 months ago
Hierarchical Bayesian Inference in Networks of Spiking Neurons
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
Rajesh P. N. Rao
WACV
2012
IEEE
13 years 5 months ago
Simultaneous inference of activity, pose and object
Human movements are important cues for recognizing human actions, which can be captured by explicit modeling and tracking of actor or through space-time low-level features. Howeve...
Furqan M. Khan, Vivek Kumar Singh, Ram Nevatia
UAI
1996
14 years 11 months ago
Bucket elimination: A unifying framework for probabilistic inference
Probabilistic inference algorithms for belief updating, nding the most probable explanation, the maximum a posteriori hypothesis, and the maximum expected utility are reformulated...
Rina Dechter
CORR
2012
Springer
187views Education» more  CORR 2012»
13 years 5 months ago
Sequential Inference for Latent Force Models
Latent force models (LFMs) are hybrid models combining mechanistic principles with non-parametric components. In this article, we shall show how LFMs can be equivalently formulate...
Jouni Hartikainen, Simo Särkkä
NIPS
2003
14 years 11 months ago
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
Radford M. Neal, Matthew J. Beal, Sam T. Roweis