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- Frank R. Kschischang, Brendan J. Frey, Hans-Andrea Loeliger
- IEEE Trans. Information Theory
- 2001

|A factor graph is a bipartite graph that expresses how a \global" function of many variables factors into a product of \local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random elds, and Tanner graphs. Following one simple computational rule, the sum-product algorithm operates in factor graphs to… (More)

- Brendan J Frey, Delbert Dueck
- Science
- 2007

Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such "exemplars" can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initial choice is close to a good solution. We devised a method… (More)

This thesis develops two Bayesian learning methods relying on Gaussian processes and a rigorous statistical approach for evaluating such methods. In these experimental designs the sources of uncertainty in the estimated generalisation performances due to both variation in training and test sets are accounted for. The framework allows for estimation of… (More)

- G E Hinton, P Dayan, B J Frey, R M Neal
- Science
- 1995

An unsupervised learning algorithm for a multilayer network of stochastic neurons is described. Bottom-up "recognition" connections convert the input into representations in successive hidden layers, and top-down "generative" connections reconstruct the representation in one layer from the representation in the layer above. In the "wake" phase, neurons are… (More)

- Nebojsa Jojic, Brendan J. Frey
- CVPR
- 2001

See a PPT file with videos at

- Brendan J. Frey, Nebojsa Jojic
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2003

—Clustering is a simple, effective way to derive useful representations of data, such as images and videos. Clustering explains the input as one of several prototypes, plus noise. In situations where each input has been randomly transformed (e.g., by translation, rotation, and shearing in images and videos), clustering techniques tend to extract cluster… (More)

- Debashish Ray, Hilal Kazan, +32 authors Timothy R. Hughes
- Nature
- 2013

RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary… (More)

- Nebojsa Jojic, Brendan J. Frey, Anitha Kannan
- ICCV
- 2003

See www.research.microsoft.com/∼jojic/epitome.htm for videos, comparisons and applications. We present novel simple appearance and shape models that we call epitomes. The epitome of an image is its miniature, condensed version containing the essence of the textural and shape properties of the image. As opposed to previously used simple image models, such as… (More)

- Brendan J. Frey, Nebojsa Jojic
- IEEE Transactions on Pattern Analysis and Machine…
- 2005

Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face… (More)

- Brendan J. Frey, David J. C. MacKay
- NIPS
- 1997

• In Until recently, artificial intelligence researchers have frowned upon the application of probability propagation in Bayesian belief networks that have cycles. The probability propagation algorithm is only exact in networks that are cycle-free. However, it has recently been discovered that the two best error-correcting decoding algorithms are actually… (More)