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Jeff A Bilmes

Showing results (1-10 of 14) with videos related to

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Advances in Neural Information Processing Systems|February 2, 2019
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular FunctionsWenruo Bai, William S Noble, Jeff A Bilmes
Plos Computational Biology|July 15, 2010
Learning a weighted sequence model of the nucleosome core and linker yields more accurate predictions in Saccharomyces cerevisiae and Homo sapiensSheila M Reynolds, Jeff A Bilmes, William Stafford Noble
Journal of Proteome Research|July 12, 2016
Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass SpectraJohn T Halloran, Jeff A Bilmes, William S Noble
Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence|October 10, 2014
Learning Peptide-Spectrum Alignment Models for Tandem Mass SpectrometryJohn T Halloran, Jeff A Bilmes, William S Noble
Bioinformatics (Oxford, England)|June 17, 2016
Faster and more accurate graphical model identification of tandem mass spectra using trellisesShengjie Wang, John T Halloran, Jeff A Bilmes, et al.
Disability and Rehabilitation. Assistive Technology|April 18, 2008
The Vocal Joystick: evaluation of voice-based cursor control techniques for assistive technologySusumu Harada, James A Landay, Jonathan Malkin, et al.
Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence|November 11, 2014
Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass SpectraAjit P Singh, John Halloran, Jeff A Bilmes, et al.
Bioinformatics (Oxford, England)|June 10, 2010
A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing dataXiaoyu Chen, Michael M Hoffman, Jeff A Bilmes, et al.
Plos Computational Biology|November 8, 2008
Transmembrane topology and signal peptide prediction using dynamic bayesian networksSheila M Reynolds, Lukas Käll, Michael E Riffle, et al.
Bioinformatics (Oxford, England)|July 1, 2008
Modeling peptide fragmentation with dynamic Bayesian networks for peptide identificationAaron A Klammer, Sheila M Reynolds, Jeff A Bilmes, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Advances in Neural Information Processing Systems|February 2, 2019
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular FunctionsWenruo Bai, William S Noble, Jeff A Bilmes
Plos Computational Biology|July 15, 2010
Learning a weighted sequence model of the nucleosome core and linker yields more accurate predictions in Saccharomyces cerevisiae and Homo sapiensSheila M Reynolds, Jeff A Bilmes, William Stafford Noble
Journal of Proteome Research|July 12, 2016
Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass SpectraJohn T Halloran, Jeff A Bilmes, William S Noble
Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence|October 10, 2014
Learning Peptide-Spectrum Alignment Models for Tandem Mass SpectrometryJohn T Halloran, Jeff A Bilmes, William S Noble
Bioinformatics (Oxford, England)|June 17, 2016
Faster and more accurate graphical model identification of tandem mass spectra using trellisesShengjie Wang, John T Halloran, Jeff A Bilmes, et al.
Disability and Rehabilitation. Assistive Technology|April 18, 2008
The Vocal Joystick: evaluation of voice-based cursor control techniques for assistive technologySusumu Harada, James A Landay, Jonathan Malkin, et al.
Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence|November 11, 2014
Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass SpectraAjit P Singh, John Halloran, Jeff A Bilmes, et al.
Bioinformatics (Oxford, England)|June 10, 2010
A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing dataXiaoyu Chen, Michael M Hoffman, Jeff A Bilmes, et al.
Plos Computational Biology|November 8, 2008
Transmembrane topology and signal peptide prediction using dynamic bayesian networksSheila M Reynolds, Lukas Käll, Michael E Riffle, et al.
Bioinformatics (Oxford, England)|July 1, 2008
Modeling peptide fragmentation with dynamic Bayesian networks for peptide identificationAaron A Klammer, Sheila M Reynolds, Jeff A Bilmes, et al.
Pageof 2