Kevin P. Murphy

- Research Area(s)
- Machine Intelligence
- Machine Perception
Co-Authors
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Alex Alemi
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Alexander Gorban
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Alexander Toshev
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Alireza Fathi
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Andrew Rabinovich
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Anoop Korattikara
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Chen Sun
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Chris Bregler
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Evgeniy Gabrilovich
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Forrester Cole
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Fred Bertsch
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Gal Chechik
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George Papandreou
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Hartmut Neven
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Hartwig Adam
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Hyun Oh Song
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Ian Fischer
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Inbar Mosseri
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Jonathan Huang
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Jonathon Shlens
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Julian Ibarz
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Konstantinos Bousmalis
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Menglong Zhu
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Mohammad Norouzi
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Nan Ding
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Ni Lao
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Nick Johnston
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Rahul Gupta
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Sami Abu-El-Haija
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Samy Bengio
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Sergio Guadarrama
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Stephan Gouws
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Xin Luna Dong
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Yang Song
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Yangqing Jia
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Zbigniew Wojna
Google Publications
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Attention-based Extraction of Structured Information from Street View Imagery
Zbigniew Wojna, Alex Gorban, Dar-Shyang Lee, Kevin Murphy, Qian Yu, Yeqing Li, Julian Ibarz
ICDAR (2017), pp. 8
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Context-aware Captions from Context-agnostic Supervision
Shanmukha Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik
CVPR (2017)
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Deep Metric Learning via Facility Location
Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy
IEEE CVPR (2017)
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Deep Variational Information Bottleneck
Alex Alemi, Ian Fischer, Josh Dillon, Kevin Murphy
ICLR (2017)
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PixColor: Pixel Recursive Colorization
Sergio Guadarrama, Ryan Dahl, David Bieber, Mohammad Norouzi, Jonathon Shlens, Kevin Murphy
Proceedings of the 28th British Machine Vision Conference (BMVC) (2017)
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Speed and accuracy trade-offs for modern convolutional object detectors
Alireza Fathi, Anoop Korattikara, Chen Sun, Ian Fischer, Jonathan Huang, Kevin Murphy, Menglong Zhu, Sergio Guadarrama, Vivek Rathod, Yang Song, Zbigniew Wojna
CVPR 2017, Honolulu, Hawaii (2017)
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Towards Accurate Multi-person Pose Estimation in the Wild
George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, Kevin Murphy
CVPR (2017)
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XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings
Amelie Royer, Konstantinos Bousmalis, Stephan Gouws, Fred Bertsch, Inbar Mosseri, Forrester Cole, Kevin Murphy
arXiv (2017)
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Detecting Events and Key Actors in Multi-Person Videos
Vignesh Ramanathan, Jonathan Huang, Sami Abu-El-Haija, Alexander Gorban, Kevin Murphy, Li Fei-Fei
Computer Vision and Pattern Recognition (CVPR) (2016)
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Alireza Fathi, Anoop Korattikara, Chen Sun, Ian Fischer, Jonathan Huang, Kevin Murphy, Menglong Zhu, Sergio Guadarrama, Vivek Rathod, Yang Song, Zbigniew Wojna
2nd ImageNet and COCO Visual Recognition Challenges Joint Workshop, Amsterdam (2016)
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Generation and Comprehension of Unambiguous Object Descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev, Oana Camburu, Kevin Murphy
Computer Vision and Pattern Recognition (2016)
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Anoop Korattikara, Vivek Rathod, Kevin Murphy, Max Welling
Advances in Neural Information Processing Systems (2015)
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Im2Calories: towards an automated mobile vision food diary
Austin Myers, Nick Johnston, Vivek Rathod, Anoop Korattikara, Alex Gorban, Nathan Silberman, Sergio Guadarrama, George Papandreou, Jonathan Huang, Kevin Murphy
ICCV (2015)
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Probabilistic Label Relation Graphs with Ising Models
Nan Ding, Jia Deng, Kevin Murphy, Hartmut Neven
International Conference on Computer Vision (2015)
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What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision
Jonathan Malmaud, Jonathan Huang, Vivek Rathod, Nicholas Johnston, Andrew Rabinovich, Kevin Murphy
North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015) (to appear)
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Knowledge Base Completion via Search-Based Question Answering
Robert West, Evgeniy Gabrilovich, Kevin Murphy, Shaohua Sun, Rahul Gupta, Dekang Lin
WWW (2014)
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Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion
Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun, Wei Zhang
The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014, pp. 601-610
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Large-Scale Object Classification Using Label Relation Graphs
Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig Adam
European Conference on Computer Vision (2014)
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Machine learning: a probabilistic perspective
MIT Press, Cambridge, MA (2012)
Previous Publications
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A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy
Journal of Machine Learning Research - Proceedings Track, vol. 22 (2012), pp. 610-618
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Bayesian structure learning using dynamic programming and MCMC
Daniel Eaton, Kevin P. Murphy
CoRR, vol. abs/1206.5247 (2012)
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Group Sparse Priors for Covariance Estimation
Benjamin M. Marlin, Mark W. Schmidt, Kevin P. Murphy
CoRR, vol. abs/1205.2626 (2012)
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Identifying players in broadcast sports videos using conditional random fields
Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little
CVPR (2011), pp. 3249-3256
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Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification
David K. Duvenaud, Benjamin M. Marlin, Kevin P. Murphy
CRV (2011), pp. 371-378
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Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models
Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
ICML (2011), pp. 633-640
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Causal learning without DAGs
David K. Duvenaud, Daniel Eaton, Kevin P. Murphy, Mark W. Schmidt
Journal of Machine Learning Research - Proceedings Track, vol. 6 (2010), pp. 177-190
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Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials
Mark W. Schmidt, Kevin P. Murphy
Journal of Machine Learning Research - Proceedings Track, vol. 9 (2010), pp. 709-716
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Review of "Probabilistic graphical models" by Koller and Friedman
Artif. Intell., vol. 174 (2010), pp. 145-146
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SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors
Rodrigo Goya, Mark G. F. Sun, Ryan D. Morin, Gillian Leung, Gavin Ha, Kimberley C. Wiegand, Janine Senz, Anamaria Crisan, Marco A. Marra, Martin Hirst, David G. Huntsman, Kevin P. Murphy, Sam Aparicio, Sohrab P. Shah
Bioinformatics, vol. 26 (2010), pp. 730-736
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Time-Bounded Sequential Parameter Optimization
Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
LION (2010), pp. 281-298
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Using the forest to see the trees: exploiting context for visual object detection and localization
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Commun. ACM, vol. 53 (2010), pp. 107-114
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Variational bounds for mixed-data factor analysis
Mohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard, Kevin P. Murphy
NIPS (2010), pp. 1108-1116
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A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data
Wei-Lwun Lu, Kevin P. Murphy, James J. Little, Alla Sheffer, Hongbo Fu
IEEE T. Geoscience and Remote Sensing, vol. 47 (2009), pp. 2913-2922
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Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models
Baback Moghaddam, Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
NIPS (2009), pp. 1285-1293
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An experimental investigation of model-based parameter optimisation: SPO and beyond
Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
GECCO (2009), pp. 271-278
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Group Sparse Priors for Covariance Estimation
Benjamin M. Marlin, Mark W. Schmidt, Kevin P. Murphy
UAI (2009), pp. 383-392
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Model-based clustering of array CGH data
Sohrab P. Shah, K-John Cheung Jr., Nathalie A. Johnson, Guillaume Alain, Randy D. Gascoyne, Douglas E. Horsman, Raymond T. Ng, Kevin P. Murphy
Bioinformatics, vol. 25 (2009)
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Modeling Discrete Interventional Data using Directed Cyclic Graphical Models
Mark W. Schmidt, Kevin P. Murphy
UAI (2009), pp. 487-495
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Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm
Mark W. Schmidt, Ewout van den Berg, Michael P. Friedlander, Kevin P. Murphy
Journal of Machine Learning Research - Proceedings Track, vol. 5 (2009), pp. 456-463
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Sparse Gaussian graphical models with unknown block structure
Benjamin M. Marlin, Kevin P. Murphy
ICML (2009), pp. 89
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LabelMe: A Database and Web-Based Tool for Image Annotation
Bryan C. Russell, Antonio Torralba, Kevin P. Murphy, William T. Freeman
International Journal of Computer Vision, vol. 77 (2008), pp. 157-173
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Structure learning in random fields for heart motion abnormality detection
Mark W. Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales
CVPR (2008)
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A non-myopic approach to visual search
Julia Vogel, Kevin P. Murphy
CRV (2007), pp. 227-234
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Bayesian structure learning using dynamic programming and MCMC
Daniel Eaton, Kevin P. Murphy
UAI (2007), pp. 101-108
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Efficient parameter estimation for RNA secondary structure prediction
Mirela Andronescu, Anne Condon, Holger H. Hoos, David H. Mathews, Kevin P. Murphy
ISMB/ECCB (Supplement of Bioinformatics) (2007), pp. 19-28
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Exact Bayesian structure learning from uncertain interventions
Daniel Eaton, Kevin P. Murphy
Journal of Machine Learning Research - Proceedings Track, vol. 2 (2007), pp. 107-114
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Figure-ground segmentation using a hierarchical conditional random field
Jordan Reynolds, Kevin P. Murphy
CRV (2007), pp. 175-182
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Learning Graphical Model Structure Using L1-Regularization Paths
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy
AAAI (2007), pp. 1278-1283
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Modeling changing dependency structure in multivariate time series
Xiang Xuan, Kevin P. Murphy
ICML (2007), pp. 1055-1062
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Modeling recurrent DNA copy number alterations in array CGH data
Sohrab P. Shah, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy
ISMB/ECCB (Supplement of Bioinformatics) (2007), pp. 450-458
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Sharing Visual Features for Multiclass and Multiview Object Detection
Antonio Torralba, Kevin P. Murphy, William T. Freeman
IEEE Trans. Pattern Anal. Mach. Intell., vol. 29 (2007), pp. 854-869
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Accelerated training of conditional random fields with stochastic gradient methods
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
ICML (2006), pp. 969-976
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Integrating copy number polymorphisms into array CGH analysis using a robust HMM
Sohrab P. Shah, Xiang Xuan, Ronald J. deLeeuw, Mehrnoush Khojasteh, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy
ISMB (Supplement of Bioinformatics) (2006), pp. 431-439
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Object Detection and Localization Using Local and Global Features
Kevin P. Murphy, Antonio Torralba, Daniel Eaton, William T. Freeman
Toward Category-Level Object Recognition (2006), pp. 382-400
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Shared Features for Multiclass Object Detection
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Toward Category-Level Object Recognition (2006), pp. 345-361
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Contextual Models for Object Detection Using Boosted Random Fields
Antonio Torralba, Kevin P. Murphy, William T. Freeman
NIPS (2004)
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Representing Hierarchical POMDPs as DBNs for Multi-scale Robot Localization
Georgios Theocharous, Kevin P. Murphy, Leslie Pack Kaelbling
ICRA (2004), pp. 1045-1051
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Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection
Antonio Torralba, Kevin P. Murphy, William T. Freeman
CVPR (2) (2004), pp. 762-769
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Context-based vision system for place and object recognition
Antonio Torralba, Kevin P. Murphy, William T. Freeman, Mark A. Rubin
ICCV (2003), pp. 273-280
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Graphical Model For Recognizing Scenes and Objects
Kevin P. Murphy, Antonio Torralba, William T. Freeman
NIPS (2003)
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A coupled HMM for audio-visual speech recognition
Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxiang Liu, Crusoe Mao, Kevin P. Murphy
ICASSP (2002), pp. 2013-2016
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Dynamic Bayesian Networks for Audio-Visual Speech Recognition
Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxing Liu, Kevin P. Murphy
EURASIP J. Adv. Sig. Proc., vol. 2002 (2002), pp. 1274-1288
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Linear-time inference in Hierarchical HMMs
Kevin P. Murphy, Mark A. Paskin
NIPS (2001), pp. 833-840
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The Factored Frontier Algorithm for Approximate Inference in DBNs
Kevin P. Murphy, Yair Weiss
UAI (2001), pp. 378-385
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Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell
UAI (2000), pp. 176-183
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A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy
ICCV (1999), pp. 94-101
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A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables
UAI (1999), pp. 457-466
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Bayesian Map Learning in Dynamic Environments
NIPS (1999), pp. 1015-1021
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Loopy Belief Propagation for Approximate Inference: An Empirical Study
Kevin P. Murphy, Yair Weiss, Michael I. Jordan
UAI (1999), pp. 467-475
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Vision-Based Speaker Detection Using Bayesian Networks
James M. Rehg, Kevin P. Murphy, Paul W. Fieguth
CVPR (1999), pp. 2110-2116
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Learning the Structure of Dynamic Probabilistic Networks
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
UAI (1998), pp. 139-147
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Space-Efficient Inference in Dynamic Probabilistic Networks
John Binder, Kevin P. Murphy, Stuart J. Russell
IJCAI (1997), pp. 1292-1296
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Automata-Theoretic Models of Mutation and Alignment
David B. Searls, Kevin P. Murphy
ISMB (1995), pp. 341-349