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ENGL
2007
75views more  ENGL 2007»
15 years 6 months ago
Uncertainty Modeling for Expensive Functions: A Rank Transformation Approach
An uncertainty model for an expensive function greatly improves the effectiveness of a design decision based on the use of a less accurate function. In this paper, we propose a met...
J. Umakant, K. Sudhakar, P. M. Mujumdar, C. Raghav...
226
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JCB
2000
146views more  JCB 2000»
15 years 6 months ago
Bayesian Segmentation of Protein Secondary Structure
We present a novel method for predicting the secondary structure of a protein from its amino acid sequence. Most existing methods predict each position in turn based on a local wi...
Scott C. Schmidler, Jun S. Liu, Douglas L. Brutlag
JCNS
1998
134views more  JCNS 1998»
15 years 6 months ago
Analytical and Simulation Results for Stochastic Fitzhugh-Nagumo Neurons and Neural Networks
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...
Henry C. Tuckwell, Roger Rodriguez
PAMI
2010
205views more  PAMI 2010»
15 years 5 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
TROB
2010
129views more  TROB 2010»
15 years 5 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...