Kevin P. Murphy

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 10

Top Topics

Pose Estimation

Unsupervised Learning

Dynamical Systems

Top Venues

Publications

Miguel Lázaro-Gredilla, Li Yang Ku, Kevin P. Murphy, Dileep George
What type of inference is planning? CoRR (2024)
Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations. NeurIPS (2023)
Lijun Yu, Yong Cheng, Zhiruo Wang, Vivek Kumar, Wolfgang Macherey, Yanping Huang, David A. Ross, Irfan Essa, Yonatan Bisk, Ming-Hsuan Yang, Kevin P. Murphy, Alexander G. Hauptmann, Lu Jiang
SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs. NeurIPS (2023)
Junwei Liang, Lu Jiang, Kevin P. Murphy, Ting Yu, Alexander G. Hauptmann
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction. CVPR (2020)
Zhe Dong, Bryan A. Seybold, Kevin P. Murphy, Hung H. Bui
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems. CoRR (2019)
Junwei Liang, Lu Jiang, Kevin P. Murphy, Ting Yu, Alexander G. Hauptmann
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction. CoRR (2019)
Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee
Unsupervised learning of object structure and dynamics from videos. NeurIPS (2019)
Seong Joon Oh, Kevin P. Murphy, Jiyan Pan, Joseph Roth, Florian Schroff, Andrew C. Gallagher
Modeling Uncertainty with Hedged Instance Embeddings. ICLR (Poster) (2019)
George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, Kevin P. Murphy
Towards Accurate Multi-person Pose Estimation in the Wild. CoRR (2017)
Alireza Fathi, Zbigniew Wojna, Vivek Rathod, Peng Wang, Hyun Oh Song, Sergio Guadarrama, Kevin P. Murphy
Semantic Instance Segmentation via Deep Metric Learning. CoRR (2017)
Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy, Max Welling
Bayesian dark knowledge. NIPS (2015)
Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven
Probabilistic Label Relation Graphs with Ising Models. ICCV (2015)
George Papandreou, Liang-Chieh Chen, Kevin P. Murphy, Alan L. Yuille
Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation. ICCV (2015)
Kevin P. Murphy, Yair Weiss, Michael I. Jordan
Loopy Belief Propagation for Approximate Inference: An Empirical Study CoRR (2013)
Kevin P. Murphy
A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables CoRR (2013)
Kevin P. Murphy, Yair Weiss
The Factored Frontier Algorithm for Approximate Inference in DBNs CoRR (2013)
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
Learning the Structure of Dynamic Probabilistic Networks CoRR (2013)
Nando de Freitas, Kevin P. Murphy
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (2012) CoRR (2013)
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks CoRR (2013)
Wei-Lwun Lu, Jo-Anne Ting, James J. Little, Kevin P. Murphy
Learning to Track and Identify Players from Broadcast Sports Videos. IEEE Trans. Pattern Anal. Mach. Intell. 35 (7) (2013)
Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression. NIPS (2012)
Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy
Group Sparse Priors for Covariance Estimation CoRR (2012)
Mark Schmidt, Kevin P. Murphy
Modeling Discrete Interventional Data using Directed Cyclic Graphical Models CoRR (2012)
Daniel Eaton, Kevin P. Murphy
Bayesian structure learning using dynamic programming and MCMC CoRR (2012)
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models. AISTATS (2012)
David Duvenaud, Benjamin M. Marlin, Kevin P. Murphy
Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification. CRV (2011)
Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models. ICML (2011)
Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little
Identifying players in broadcast sports videos using conditional random fields. CVPR (2011)
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
SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors. Bioinform. 26 (6) (2010)
David C. Sharp, Alex E. Bell, Jeffrey J. Gold, Ken W. Gibbar, Dennis W. Gvillo, Vann M. Knight, Kevin P. Murphy, Wendy Roll, Radhakrishna G. Sampigethaya, Viswa Santhanam, Steven P. Weismuller
Challenges and Solutions for Embedded and Networked Aerospace Software Systems. Proc. IEEE 98 (4) (2010)
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Using the forest to see the trees: exploiting context for visual object detection and localization. Commun. ACM 53 (3) (2010)
Mark Schmidt, Kevin P. Murphy
Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials. AISTATS (2010)
Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
Time-Bounded Sequential Parameter Optimization. LION (2010)
David Duvenaud, Daniel Eaton, Kevin P. Murphy, Mark Schmidt
Causal learning without DAGs. NIPS Causality: Objectives and Assessment (2010)
Kevin P. Murphy
Review of "Probabilistic graphical models" by Koller and Friedman. Artif. Intell. 174 (2) (2010)
Mohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard, Kevin P. Murphy
Variational bounds for mixed-data factor analysis. NIPS (2010)
Mark Schmidt, Ewout van den Berg, Michael P. Friedlander, Kevin P. Murphy
Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm. AISTATS (2009)
Benjamin M. Marlin, Kevin P. Murphy
Sparse Gaussian graphical models with unknown block structure. ICML (2009)
Baback Moghaddam, Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models. NIPS (2009)
Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
An experimental investigation of model-based parameter optimisation: SPO and beyond. GECCO (2009)
Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy
Group Sparse Priors for Covariance Estimation. UAI (2009)
Sohrab P. Shah, K-John Cheung Jr., Nathalie A. Johnson, Guillaume Alain, Randy D. Gascoyne, Douglas E. Horsman, Raymond T. Ng, Kevin P. Murphy
Model-based clustering of array CGH data. Bioinform. 25 (12) (2009)
Mark Schmidt, Kevin P. Murphy
Modeling Discrete Interventional Data using Directed Cyclic Graphical Models. UAI (2009)
Wei-Lwun Lu, Kevin P. Murphy, James J. Little, Alla Sheffer, Hongbo Fu
A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data. IEEE Trans. Geosci. Remote. Sens. 47 (8-2) (2009)
Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales
Structure learning in random fields for heart motion abnormality detection. CVPR (2008)
Bryan C. Russell, Antonio Torralba, Kevin P. Murphy, William T. Freeman
LabelMe: A Database and Web-Based Tool for Image Annotation. Int. J. Comput. Vis. 77 (1-3) (2008)
Sohrab P. Shah, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy
Modeling recurrent DNA copy number alterations in array CGH data. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Daniel Eaton, Kevin P. Murphy
Bayesian structure learning using dynamic programming and MCMC. UAI (2007)
Daniel Eaton, Kevin P. Murphy
Exact Bayesian structure learning from uncertain interventions. AISTATS (2007)
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Sharing Visual Features for Multiclass and Multiview Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. 29 (5) (2007)
Mirela Andronescu, Anne Condon, Holger H. Hoos, David H. Mathews, Kevin P. Murphy
Efficient parameter estimation for RNA secondary structure prediction. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Mark Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy
Learning Graphical Model Structure Using L1-Regularization Paths. AAAI (2007)
Julia Vogel, Kevin P. Murphy
A non-myopic approach to visual search. CRV (2007)
Xiang Xuan, Kevin P. Murphy
Modeling changing dependency structure in multivariate time series. ICML (2007)
Jordan Reynolds, Kevin P. Murphy
Figure-ground segmentation using a hierarchical conditional random field. CRV (2007)
Kevin P. Murphy, Antonio Torralba, Daniel Eaton, William T. Freeman
Object Detection and Localization Using Local and Global Features. Toward Category-Level Object Recognition (2006)
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
Accelerated training of conditional random fields with stochastic gradient methods. ICML (2006)
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Shared Features for Multiclass Object Detection. Toward Category-Level Object Recognition (2006)
Sohrab P. Shah, Xiang Xuan, Ronald J. deLeeuw, Mehrnoush Khojasteh, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy
Integrating copy number polymorphisms into array CGH analysis using a robust HMM. ISMB (Supplement of Bioinformatics) (2006)
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Contextual Models for Object Detection Using Boosted Random Fields. NIPS (2004)
Antonio Torralba, Kevin P. Murphy, William T. Freeman
Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection. CVPR (2) (2004)
Georgios Theocharous, Kevin P. Murphy, Leslie Pack Kaelbling
Representing Hierarchical POMDPs as DBNs for Multi-scale Robot Localization. ICRA (2004)
Kevin P. Murphy, Antonio Torralba, William T. Freeman
Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes. NIPS (2003)
Antonio Torralba, Kevin P. Murphy, William T. Freeman, Mark A. Rubin
Context-based vision system for place and object recognition. ICCV (2003)
Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxiang Liu, Crusoe Mao, Kevin P. Murphy
A coupled HMM for audio-visual speech recognition. ICASSP (2002)
Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxing Liu, Kevin P. Murphy
Dynamic Bayesian Networks for Audio-Visual Speech Recognition. EURASIP J. Adv. Signal Process. 2002 (11) (2002)
Kevin P. Murphy, Mark A. Paskin
Linear-time inference in Hierarchical HMMs. NIPS (2001)
Kevin P. Murphy, Yair Weiss
The Factored Frontier Algorithm for Approximate Inference in DBNs. UAI (2001)
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. UAI (2000)
Kevin P. Murphy
Bayesian Map Learning in Dynamic Environments. NIPS (1999)
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models. ICCV (1999)
James M. Rehg, Kevin P. Murphy, Paul W. Fieguth
Vision-Based Speaker Detection Using Bayesian Networks. CVPR (1999)
Kevin P. Murphy
A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables. UAI (1999)
Kevin P. Murphy, Yair Weiss, Michael I. Jordan
Loopy Belief Propagation for Approximate Inference: An Empirical Study. UAI (1999)
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
Learning the Structure of Dynamic Probabilistic Networks. UAI (1998)
John Binder, Kevin P. Murphy, Stuart J. Russell
Space-Efficient Inference in Dynamic Probabilistic Networks. IJCAI (1997)
David B. Searls, Kevin P. Murphy
Automata-Theoretic Models of Mutation and Alignment. ISMB (1995)