Kevin P. Murphy

87 papers A* 21A 15Misc 1Journal 27Unranked 21
YearRankTypeTitle / Venue / Authors
2026 J jnl
AutoHarness: improving LLM agents by automatically synthesizing a code harness.
CoRR
Xinghua Lou, Miguel Lázaro-Gredilla, Antoine Dedieu, Carter Wendelken, Wolfgang Lehrach, Kevin P. Murphy
2025 J jnl
Code World Models for General Game Playing.
CoRR
Wolfgang Lehrach, Daniel Hennes, Miguel Lázaro-Gredilla, Xinghua Lou, Carter Wendelken, Zun Li, Antoine Dedieu, Jordi Grau-Moya, Marc Lanctot, Atil Iscen, John Schultz, Marcus Chiam, Ian Gemp, Piotr Zielinski, Satinder Singh, Kevin P. Murphy
2024 A* conf
Bayesian Online Natural Gradient (BONG).
NeurIPS
Matt Jones, Peter G. Chang, Kevin P. Murphy
2024 A* conf
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors.
NeurIPS
Joseph Ortiz, Antoine Dedieu, Wolfgang Lehrach, J. Swaroop Guntupalli, Carter Wendelken, Ahmad Humayun, Sivaramakrishnan Swaminathan, Guangyao Zhou, Miguel Lázaro-Gredilla, Kevin P. Murphy
2024 A* conf
EM Distillation for One-step Diffusion Models.
NeurIPS
Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin P. Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
2024 J jnl
Reinforcement Learning: An Overview.
CoRR
Kevin P. Murphy
2024 A* conf
What type of inference is planning?
NeurIPS
Miguel Lázaro-Gredilla, Li Yang Ku, Kevin P. Murphy, Dileep George
2024 J jnl
What type of inference is planning?
CoRR
Miguel Lázaro-Gredilla, Li Yang Ku, Kevin P. Murphy, Dileep George
2023 A* conf
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations.
NeurIPS
Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour
2023 A* conf
SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs.
NeurIPS
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
2020 A* conf
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction.
CVPR
Junwei Liang, Lu Jiang, Kevin P. Murphy, Ting Yu, Alexander G. Hauptmann
2019 J jnl
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems.
CoRR
Zhe Dong, Bryan A. Seybold, Kevin P. Murphy, Hung H. Bui
2019 — conf
Modeling Uncertainty with Hedged Instance Embeddings.
ICLR (Poster)
Seong Joon Oh, Kevin P. Murphy, Jiyan Pan, Joseph Roth, Florian Schroff, Andrew C. Gallagher
2019 J jnl
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction.
CoRR
Junwei Liang, Lu Jiang, Kevin P. Murphy, Ting Yu, Alexander G. Hauptmann
2019 A* conf
Unsupervised learning of object structure and dynamics from videos.
NeurIPS
Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee
2017 J jnl
Semantic Instance Segmentation via Deep Metric Learning.
CoRR
Alireza Fathi, Zbigniew Wojna, Vivek Rathod, Peng Wang, Hyun Oh Song, Sergio Guadarrama, Kevin P. Murphy
2017 J jnl
Towards Accurate Multi-person Pose Estimation in the Wild.
CoRR
George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, Kevin P. Murphy
2015 — conf
Bayesian dark knowledge.
NIPS
Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy, Max Welling
2015 A* conf
Probabilistic Label Relation Graphs with Ising Models.
ICCV
Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven
2015 A* conf
Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation.
ICCV
George Papandreou, Liang-Chieh Chen, Kevin P. Murphy, Alan L. Yuille
2013 J jnl
A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables
CoRR
Kevin P. Murphy
2013 J jnl
Learning the Structure of Dynamic Probabilistic Networks
CoRR
Nir Friedman, Kevin P. Murphy, Stuart Russell
2013 J jnl
Learning to Track and Identify Players from Broadcast Sports Videos.
IEEE Trans. Pattern Anal. Mach. Intell.
Wei-Lwun Lu, Jo-Anne Ting, James J. Little, Kevin P. Murphy
2013 J jnl
Loopy Belief Propagation for Approximate Inference: An Empirical Study
CoRR
Kevin P. Murphy, Yair Weiss, Michael I. Jordan
2013 J jnl
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (2012)
CoRR
Nando de Freitas, Kevin P. Murphy
2013 J jnl
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
CoRR
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell
2013 J jnl
The Factored Frontier Algorithm for Approximate Inference in DBNs
CoRR
Kevin P. Murphy, Yair Weiss
2012 A conf
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models.
AISTATS
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy
2012 J jnl
Bayesian structure learning using dynamic programming and MCMC
CoRR
Daniel Eaton, Kevin P. Murphy
2012 — conf
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression.
NIPS
Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
2012 J jnl
Group Sparse Priors for Covariance Estimation
CoRR
Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy
2012 — book
Machine learning - a probabilistic perspective.
Kevin P. Murphy
2012 J jnl
Modeling Discrete Interventional Data using Directed Cyclic Graphical Models
CoRR
Mark Schmidt, Kevin P. Murphy
2012 A ed.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, August 14-18, 2012
UAI
Nando de Freitas, Kevin P. Murphy
2011 A* conf
Identifying players in broadcast sports videos using conditional random fields.
CVPR
Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little
2011 — conf
Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification.
CRV
David Duvenaud, Benjamin M. Marlin, Kevin P. Murphy
2011 A* conf
Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models.
ICML
Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
2010 — conf
Causal learning without DAGs.
NIPS Causality: Objectives and Assessment
David Duvenaud, Daniel Eaton, Kevin P. Murphy, Mark Schmidt
2010 J jnl
Challenges and Solutions for Embedded and Networked Aerospace Software Systems.
Proc. IEEE
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
2010 A conf
Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials.
AISTATS
Mark Schmidt, Kevin P. Murphy
2010 J jnl
Review of "Probabilistic graphical models" by Koller and Friedman.
Artif. Intell.
Kevin P. Murphy
2010 J jnl
SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors.
Bioinform.
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
2010 — ch.
Sequential Model-Based Parameter Optimization: an Experimental Investigation of Automated and Interactive Approaches.
Experimental Methods for the Analysis of Optimization Algorithms
Frank Hutter, Thomas Bartz-Beielstein, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
2010 — conf
Time-Bounded Sequential Parameter Optimization.
LION
Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
2010 J jnl
Using the forest to see the trees: exploiting context for visual object detection and localization.
Commun. ACM
Antonio Torralba, Kevin P. Murphy, William T. Freeman
2010 — conf
Variational bounds for mixed-data factor analysis.
NIPS
Mohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard, Kevin P. Murphy
2009 J jnl
A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data.
IEEE Trans. Geosci. Remote. Sens.
Wei-Lwun Lu, Kevin P. Murphy, James J. Little, Alla Sheffer, Hongbo Fu
2009 — conf
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models.
NIPS
Baback Moghaddam, Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
2009 A conf
An experimental investigation of model-based parameter optimisation: SPO and beyond.
GECCO
Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
2009 A conf
Group Sparse Priors for Covariance Estimation.
UAI
Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy
2009 J jnl
Model-based clustering of array CGH data.
Bioinform.
Sohrab P. Shah, K-John Cheung Jr., Nathalie A. Johnson, Guillaume Alain, Randy D. Gascoyne, Douglas E. Horsman, Raymond T. Ng, Kevin P. Murphy
2009 A conf
Modeling Discrete Interventional Data using Directed Cyclic Graphical Models.
UAI
Mark Schmidt, Kevin P. Murphy
2009 A conf
Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm.
AISTATS
Mark Schmidt, Ewout van den Berg, Michael P. Friedlander, Kevin P. Murphy
2009 A* conf
Sparse Gaussian graphical models with unknown block structure.
ICML
Benjamin M. Marlin, Kevin P. Murphy
2008 J jnl
LabelMe: A Database and Web-Based Tool for Image Annotation.
Int. J. Comput. Vis.
Bryan C. Russell, Antonio Torralba, Kevin P. Murphy, William T. Freeman
2008 A* conf
Structure learning in random fields for heart motion abnormality detection.
CVPR
Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales
2007 — conf
A non-myopic approach to visual search.
CRV
Julia Vogel, Kevin P. Murphy
2007 A conf
Bayesian structure learning using dynamic programming and MCMC.
UAI
Daniel Eaton, Kevin P. Murphy
2007 — conf
Efficient parameter estimation for RNA secondary structure prediction.
ISMB/ECCB (Supplement of Bioinformatics)
Mirela Andronescu, Anne Condon, Holger H. Hoos, David H. Mathews, Kevin P. Murphy
2007 A conf
Exact Bayesian structure learning from uncertain interventions.
AISTATS
Daniel Eaton, Kevin P. Murphy
2007 — conf
Figure-ground segmentation using a hierarchical conditional random field.
CRV
Jordan Reynolds, Kevin P. Murphy
2007 A* conf
Learning Graphical Model Structure Using L1-Regularization Paths.
AAAI
Mark Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy
2007 A* conf
Modeling changing dependency structure in multivariate time series.
ICML
Xiang Xuan, Kevin P. Murphy
2007 — conf
Modeling recurrent DNA copy number alterations in array CGH data.
ISMB/ECCB (Supplement of Bioinformatics)
Sohrab P. Shah, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy
2007 J jnl
Sharing Visual Features for Multiclass and Multiview Object Detection.
IEEE Trans. Pattern Anal. Mach. Intell.
Antonio Torralba, Kevin P. Murphy, William T. Freeman
2006 A* conf
Accelerated training of conditional random fields with stochastic gradient methods.
ICML
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
2006 — conf
Integrating copy number polymorphisms into array CGH analysis using a robust HMM.
ISMB (Supplement of Bioinformatics)
Sohrab P. Shah, Xiang Xuan, Ronald J. deLeeuw, Mehrnoush Khojasteh, Wan L. Lam, Raymond T. Ng, Kevin P. Murphy
2006 — conf
Object Detection and Localization Using Local and Global Features.
Toward Category-Level Object Recognition
Kevin P. Murphy, Antonio Torralba, Daniel Eaton, William T. Freeman
2006 — conf
Shared Features for Multiclass Object Detection.
Toward Category-Level Object Recognition
Antonio Torralba, Kevin P. Murphy, William T. Freeman
2004 — conf
Contextual Models for Object Detection Using Boosted Random Fields.
NIPS
Antonio Torralba, Kevin P. Murphy, William T. Freeman
2004 A* conf
Representing Hierarchical POMDPs as DBNs for Multi-scale Robot Localization.
ICRA
Georgios Theocharous, Kevin P. Murphy, Leslie Pack Kaelbling
2004 — conf
Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection.
CVPR (2)
Antonio Torralba, Kevin P. Murphy, William T. Freeman
2003 A* conf
Context-based vision system for place and object recognition.
ICCV
Antonio Torralba, Kevin P. Murphy, William T. Freeman, Mark A. Rubin
2003 — conf
Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes.
NIPS
Kevin P. Murphy, Antonio Torralba, William T. Freeman
2002 Misc conf
A coupled HMM for audio-visual speech recognition.
ICASSP
Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxiang Liu, Crusoe Mao, Kevin P. Murphy
2002 J jnl
Dynamic Bayesian Networks for Audio-Visual Speech Recognition.
EURASIP J. Adv. Signal Process.
Ara V. Nefian, Luhong Liang, Xiaobo Pi, Xiaoxing Liu, Kevin P. Murphy
2001 — conf
Linear-time inference in Hierarchical HMMs.
NIPS
Kevin P. Murphy, Mark A. Paskin
2001 A conf
The Factored Frontier Algorithm for Approximate Inference in DBNs.
UAI
Kevin P. Murphy, Yair Weiss
2000 A conf
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.
UAI
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell
1999 A* conf
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models.
ICCV
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Kevin P. Murphy
1999 A conf
A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables.
UAI
Kevin P. Murphy
1999 — conf
Bayesian Map Learning in Dynamic Environments.
NIPS
Kevin P. Murphy
1999 A conf
Loopy Belief Propagation for Approximate Inference: An Empirical Study.
UAI
Kevin P. Murphy, Yair Weiss, Michael I. Jordan
1999 A* conf
Vision-Based Speaker Detection Using Bayesian Networks.
CVPR
James M. Rehg, Kevin P. Murphy, Paul W. Fieguth
1998 A conf
Learning the Structure of Dynamic Probabilistic Networks.
UAI
Nir Friedman, Kevin P. Murphy, Stuart Russell
1997 — conf
Space-Efficient Inference in Dynamic Probabilistic Networks.
IJCAI
John Binder, Kevin P. Murphy, Stuart Russell
1995 A conf
Automata-Theoretic Models of Mutation and Alignment.
ISMB
David B. Searls, Kevin P. Murphy