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» Learning for stochastic dynamic programming
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UM
2009
Springer
15 years 9 months ago
Just-in-Time Adaptivity through Dynamic Items
Adaptive course generation becomes more appropriate for realistic usage scenarios and more flexible if it includes mechanisms deciding just-in-time which content, which exercises,...
Carsten Ullrich, Tianxiang Lu, Erica Melis
124
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CGI
2006
IEEE
15 years 8 months ago
Quasi-physical Simulation of Large-Scale Dynamic Forest Scenes
This paper presents a quasi-physically based approach for interactively simulating large-scale dynamic forest scenes under different wind conditions. We introduce theories from th...
Long Zhang, Chengfang Song, Qifeng Tan, Wei Chen, ...
112
Voted
JCC
2008
105views more  JCC 2008»
15 years 2 months ago
Retrieval of spectral and dynamic properties from two-dimensional infrared pump-probe experiments
Abstract: We have developed a fitting algorithm able to extract spectral and dynamic properties of a three level oscillator from a two-dimensional infrared spectrum (2D-IR) detecte...
Riccardo Chelli, Victor V. Volkov, Roberto Righini
131
Voted
BMCBI
2005
99views more  BMCBI 2005»
15 years 2 months ago
Effective ambiguity checking in biosequence analysis
Background: Ambiguity is a problem in biosequence analysis that arises in various analysis tasks solved via dynamic programming, and in particular, in the modeling of families of ...
Janina Reeder, Peter Steffen, Robert Giegerich
142
Voted
BMCBI
2010
229views more  BMCBI 2010»
15 years 2 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck