Murphy, Kevin P.

38 publications

NeurIPS 2024 What Type of Inference Is Planning? Miguel Lázaro-Gredilla, Li Yang Ku, Kevin P. Murphy, Dileep George

NeurIPS 2023 Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour

NeurIPS 2023 SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs Lijun Yu, Yong Cheng, Zhiruo Wang, Vivek Kumar, Wolfgang Macherey, Yanping Huang, David A. Ross, Irfan A. Essa, Yonatan Bisk, Ming-Hsuan Yang, Kevin P. Murphy, Alexander Hauptmann, Lu Jiang

NeurIPS 2019 Language as an Abstraction for Hierarchical Deep Reinforcement Learning YiDing Jiang, Shixiang Gu, Kevin P. Murphy, Chelsea Finn

ICLR 2019 Modeling Uncertainty with Hedged Instance Embeddings Seong Joon Oh, Kevin P. Murphy, Jiyan Pan, Joseph Roth, Florian Schroff, Andrew C. Gallagher

NeurIPS 2019 Unsupervised Learning of Object Structure and Dynamics from Videos Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee

NeurIPS 2015 Bayesian Dark Knowledge Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy, Max Welling

ICCV 2015 Im2Calories: Towards an Automated Mobile Vision Food Diary Austin Meyers, Nick Johnston, Vivek Rathod, Anoop Korattikara, Alex Gorban, Nathan Silberman, Sergio Guadarrama, George Papandreou, Jonathan Huang, Kevin P. Murphy

ICCV 2015 Probabilistic Label Relation Graphs with Ising Models Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven

ICCV 2015 Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation George Papandreou, Liang-Chieh Chen, Kevin P. Murphy, Alan L. Yuille

NeurIPS 2012 Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy

UAI 2012 Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, August 14-18, 2012 Nando de Freitas, Kevin P. Murphy

CVPR 2011 Identifying Players in Broadcast Sports Videos Using Conditional Random Fields Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little

ICML 2011 Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy

NeurIPS 2010 Variational Bounds for Mixed-Data Factor Analysis Mohammad Emtiyaz Khan, Guillaume Bouchard, Kevin P. Murphy, Benjamin M. Marlin

NeurIPS 2009 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models Baback Moghaddam, Mohammad Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin

UAI 2009 Group Sparse Priors for Covariance Estimation Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy

UAI 2009 Modeling Discrete Interventional Data Using Directed Cyclic Graphical Models Mark Schmidt, Kevin P. Murphy

ICML 2009 Sparse Gaussian Graphical Models with Unknown Block Structure Benjamin M. Marlin, Kevin P. Murphy

CVPR 2008 Structure Learning in Random Fields for Heart Motion Abnormality Detection Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales

UAI 2007 Bayesian Structure Learning Using Dynamic Programming and MCMC Daniel Eaton, Kevin P. Murphy

AAAI 2007 Learning Graphical Model Structure Using L1-Regularization Paths Mark Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy

ICML 2007 Modeling Changing Dependency Structure in Multivariate Time Series Xiang Xuan, Kevin P. Murphy

ICML 2006 Accelerated Training of Conditional Random Fields with Stochastic Gradient Methods S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy

NeurIPS 2004 Contextual Models for Object Detection Using Boosted Random Fields Antonio Torralba, Kevin P. Murphy, William T. Freeman

CVPR 2004 Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection Antonio Torralba, Kevin P. Murphy, William T. Freeman

ICCV 2003 Context-Based Vision System for Place and Object Recognition Antonio Torralba, Kevin P. Murphy, William T. Freeman, Mark A. Rubin

NeurIPS 2003 Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes Kevin P. Murphy, Antonio Torralba, William T. Freeman

NeurIPS 2001 Linear-Time Inference in Hierarchical HMMs Kevin P. Murphy, Mark A. Paskin

UAI 2001 The Factored Frontier Algorithm for Approximate Inference in DBNs Kevin P. Murphy, Yair Weiss

UAI 2000 Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell

ICCV 1999 A Dynamic Bayesian Network Approach to Figure Tracking Using Learned Dynamic Models Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy

UAI 1999 A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables Kevin P. Murphy

NeurIPS 1999 Bayesian mAP Learning in Dynamic Environments Kevin P. Murphy

UAI 1999 Loopy Belief Propagation for Approximate Inference: An Empirical Study Kevin P. Murphy, Yair Weiss, Michael I. Jordan

CVPR 1999 Vision-Based Speaker Detection Using Bayesian Networks James M. Rehg, Kevin P. Murphy, Paul W. Fieguth

UAI 1998 Learning the Structure of Dynamic Probabilistic Networks Nir Friedman, Kevin P. Murphy, Stuart Russell

IJCAI 1997 Space-Efficient Inference in Dynamic Probabilistic Networks John Binder, Kevin P. Murphy, Stuart Russell