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AI
2007
Springer
14 years 1 months ago
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Changhe Yuan, Marek J. Druzdzel
RT
2005
Springer
14 years 26 days ago
Importance Resampling for Global Illumination
This paper develops importance resampling into a variance reduction technique for Monte Carlo integration. Importance resampling is a sample generation technique that can be used ...
Justin Talbot, David Cline, Parris K. Egbert
UAI
2003
13 years 8 months ago
An Importance Sampling Algorithm Based on Evidence Pre-propagation
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
Changhe Yuan, Marek J. Druzdzel
RT
2005
Springer
14 years 26 days ago
Bidirectional Importance Sampling for Direct Illumination
Image-based representations for illumination can capture complex real-world lighting that is difficult to represent in other forms. Current importance sampling strategies for ima...
David Burke, Abhijeet Ghosh, Wolfgang Heidrich
VMV
2000
146views Visualization» more  VMV 2000»
13 years 8 months ago
Efficient Importance Sampling Techniques for the Photon Map
In global illumination computations the photon map is a powerful tool for approximating the irradiance, which is stored independent from scene geometry. By presenting a new algori...
Alexander Keller, Ingo Wald