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NIPS
2007
14 years 11 days ago
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Charlie Frogner, Avi Pfeffer
EH
2005
IEEE
127views Hardware» more  EH 2005»
14 years 4 months ago
On the Robustness Achievable with Stochastic Development Processes
Manufacturing processes are a key source of faults in complex hardware systems. Minimizing this impact of manufacturing uncertainties is one way towards achieving fault tolerant s...
Shivakumar Viswanathan, Jordan B. Pollack
IOR
2006
192views more  IOR 2006»
13 years 11 months ago
Exact Simulation of Stochastic Volatility and Other Affine Jump Diffusion Processes
The stochastic differential equations for affine jump diffusion models do not yield exact solutions that can be directly simulated. Discretization methods can be used for simulati...
Mark Broadie, Özgür Kaya
CORR
2010
Springer
84views Education» more  CORR 2010»
13 years 11 months ago
Left-Inverses of Fractional Laplacian and Sparse Stochastic Processes
The fractional Laplacian (-)/2 commutes with the primary coordination transformations in the Euclidean space Rd: dilation, translation and rotation, and has tight link to splines, ...
Qiyu Sun, Michael Unser
JCNS
2000
67views more  JCNS 2000»
13 years 10 months ago
Renewal-Process Approximation of a Stochastic Threshold Model for Electrical Neural Stimulation
In a recent set of modeling studies we have developed a stochastic threshold model of auditory nerve response to single biphasic electrical pulses (Bruce et al., 1999c) and moderat...
Ian C. Bruce, Laurence S. Irlicht, Mark W. White, ...