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Cited By
- Vats D and Nowak R (2014). A junction tree framework for undirected graphical model selection, The Journal of Machine Learning Research, 15:1, (147-191), Online publication date: 1-Jan-2014.
- Oka A and Lampe L (2019). Incremental distributed identification of Markov random field models in wireless sensor networks, IEEE Transactions on Signal Processing, 57:6, (2396-2405), Online publication date: 1-Jun-2009.
- Sutton C, McCallum A and Rohanimanesh K (2007). Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data, The Journal of Machine Learning Research, 8, (693-723), Online publication date: 1-May-2007.
- Caetano T, Caelli T, Schuurmans D and Barone D (2006). Graphical Models and Point Pattern Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, 28:10, (1646-1663), Online publication date: 1-Oct-2006.
- Wainwright M, Jaakkola T and Willsky A (2019). Tree consistency and bounds on the performance of the max-product algorithm and its generalizations, Statistics and Computing, 14:2, (143-166), Online publication date: 1-Apr-2004.
- Sutton C, Rohanimanesh K and McCallum A Dynamic conditional random fields Proceedings of the twenty-first international conference on Machine learning
- Delouille V, Neelamani R and Baraniuk R Robust distributed estimation in sensor networks using the embedded polygons algorithm Proceedings of the 3rd international symposium on Information processing in sensor networks, (405-413)
- Wainwright M, Jaakkola T and Willsky A A new class of upper bounds on the log partition function Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence, (536-543)
Index Terms
- Stochastic processes on graphs with cycles: geometric and variational approaches
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