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UAI
2003
14 years 6 days ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
VMV
2003
173views Visualization» more  VMV 2003»
14 years 6 days ago
Improved Hardware-Accelerated Visual Hull Rendering
The visual hull is an efficient shape approximation for the purpose of reconstructing and visualizing dynamic objects. Recently, rapid progress in graphics hardware development h...
Ming Li, Marcus A. Magnor, Hans-Peter Seidel
UAI
2000
14 years 6 days ago
Fast Planning in Stochastic Games
Stochastic games generalize Markov decision processes MDPs to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards de...
Michael J. Kearns, Yishay Mansour, Satinder P. Sin...
UAI
1996
14 years 5 days ago
A Qualitative Markov Assumption and Its Implications for Belief Change
The study of belief change has been an active area in philosophy and AI. In recent years, two special cases of belief change, belief revision and belief update, have been studied ...
Nir Friedman, Joseph Y. Halpern
GCB
2008
Springer
103views Biometrics» more  GCB 2008»
13 years 12 months ago
Utilizing Promoter Pair Orientations for HMM-based Analysis of ChIP-chip Data
: Array-based analysis of chromatin immunoprecipitation data (ChIP-chip) is a powerful technique for identifying DNA target regions of individual transcription factors. Here, we pr...
Michael Seifert, Jens Keilwagen, Marc Strickert, I...