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2007

L. Zhu, Y. Chao, and A.L. Yuille. ``Unsupervised Learning Probabilistic Grammar-Markov Model for Objects and Object-Classes''. Submitted to PAMI. 2007. pubs\ucla\C9_lzhu_PAMISUB2007.pdf

J. J. Corso, E. Sharon, S. Dube, S. El-Saden, U. Sinha, and A. Yuille. Efficient Multilevel Brain Tumor Segmentation with Integrated Bayesian Model Classification. IEEE Transactions on Medical Imaging. To appear. 2007.pubs\ucla\C8_jcorso_TMI2007.pdf

T.L. Griffiths and A.L. Yuille, (in press). A primer on probabilistic inference. To appear in M. Oaksford and N. Chater (Eds.). The probabilistic mind: Prospects for rational models of cognition. Oxford: Oxford University Press.pubs\ucla\C7_tgriffithsBOOK2007.pdf

L. Zhu, Y. Chen, C. Lin, A.L. Yuille. "Rapid Inference on a novel AND/OR graph: Detection, Segmentation and Parsing of Articulated Deformable Objects in Cluttered Backgrounds". To appear in NIPS. 2007.pubs\ucla\C6_ychen_ANIPS2008.pdf

A.L. Yuille and HongJing Lu. "The Noisy-Logical Representation and its Application to Causal Inference". To appear in NIPS. 2007.pubs\ucla\C5_ayuille_ANIPS2008.pdf

J. Corso, A.L. Yuille, N. Sicotte, and A. Toga. Detection and Segmentation of Pathological Structures by the Extended Graph-Shifts Algorithm. To appear in MICCAI.29 Oct – 2 Nov. 2007. pubs\ucla\C4_jcorso_MICCAI2007.pdf

I. Kokkinos and A. Yuille, Unsupervised Learning of Object Deformation Models.,To appear in Proc. IEEE Int'l. Conf. on Computer Vision (ICCV), 14-20 October. 2007.pubs\ucla\C3_ikokkinos_ICCV2007.pdf

Z. Tu, S-F Zheng, and A.L. Yuille. ``Shape Matching and Registration by Data-driven EM''. To appear in Computer Vision and Image Understanding (CVIU). 2007.pubs\ucla\C2_ztu_CVIU2007.pdf

L. Zhu, Y. Chen, and A.L. Yuille. ``Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing''. In Advances in Neural Information Processing Systems 19. Cambridge, MA: MIT Press. A Bradford Book. Eds. B. Schoelkopf, Y. Weiss, and T. Hofmann. Pages 827-834. August. 2007. pubs\ucla\A214_lzhu_ANIPS2007.pdf

H-J Lu, A.L Yuille, M. Liljeholm, P.W. Cheng, and K.J. Holyoak. Bayesian models of judgments of causal strength: A comparison. In Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society (pp. 1241-1246). 1-4 August. 2007.pubs\ucla\A213_hjlu_COGSCI2007.pdf

J. J. Corso, Z. Tu, A. Yuille, and A. W. Toga. Segmentation of Sub-Cortical Structures by the Graph- Shifts Algorithm. In Proceedings of Information Processing in Medical Imaging, 183-197. 2-6 July. 2007.pubs\ucla\A212_jcorso_ipmi2007.pdf

S-F Zheng, Z. Tu, A. L. Yuille: Detecting Object Boundaries Using Low-, Mid-, and High-level Information. CVPR. 18-23 June. 2007.pubs\ucla\A211_sfzheng_CVPR2006.pdf

.Z. Tu, S-F, Zheng, A.L. Yuille, A.L. Reiss, R.A. Dutton, A.D. Lee, A.M. Galaburda, I. Dinov, P.M. Thompson and A.W. Toga. ``Automated Extraction of the Cortical Sulci Based. on a Supervised Learning Approach''. IEEE Transactions on Medical Imaging. Vol. 26. No. 4. 541-552. April 2007.pubs\ucla\A210_ztu_TMI2007.pdf

T.S. Lee and A.L. Yuille. ``Efficient Coding of Visual Scenes by Grouping and Segmentation: Theoretical Principles and Biological Evidence”. In the Bayesian Brain: Probabilistic Approaches to Neural Coding. Ed. K. Doya, S. Ishii, A. Pouget, and R.P.N. Rao. MIT Press. Pp 145-188. January 2007.pubs\ucla\A209_tlee_BAYESIAN2007.pdf.pdf

2006

Z. Tu, X. Chen, A.L. Yuille and S.C. Zhu. ``Image Parsing: Segmentation, Detection, and Recognition.'' In Towards Category-Level Object Recognition. Eds. J. Ponce, M. Hebert, C. Schmid, A. Zisserman. Springer LNCS 4170. . pp 545-576. October. 2006.pubs\ucla\A208_ztu_SPRINGER2006.pdf

J. J. Corso, E. Sharon, and A. L. Yuille. Multilevel Segmentation and Integrated Bayesian Model Classification with an Application to Brain Tumor Segmentation. In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI), volume 2, pages 790-79 pubs\ucla\A207_jcorso_MICCAI2006.pdf

S-F Zheng, Z. Tu, A.L. Yuille, A. L. Reiss, R. A. Dutton, A. D. Lee, A. M. Galaburda, P. M. Thompson, I. D. Dinov, A. W. Toga: A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci. In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI), volume 1, pages 695-703. 1-6 Oct. 2006.8. 1-6 Oct. 2006.pubs\ucla\A206_sfzheng_MICCAI2006.pdf

H-J Lu, A.L Yuille, M. Liljeholm, P.W. Cheng, and K.J. Holyoak. Modeling causal learning using Bayesian generic priors on generative and preventive powers. In R. Sun & N. Miyake (Eds.), Proceedings of the Twenty-eighth Annual Conference of the Cognitive Science Society (pp. 519-524). Mahwah, NJ: Erlbaum. 26-29 July. 2006.pubs\ucla\A205_hjlu_COGSCI2006.pdf

T.L. Griffiths and A.L. Yuille, A. A primer on probabilistic inference. Trends in Cognitive Sciences. Supplement to special issue on Probabilistic Models of Cognition (Vol 10, No. 7). July. 2006.pubs\ucla\A204_tgriffiths_chater2007.pdf

A.L. Yuille and D. Kersten. ``Vision as Bayesian Inference: Analysis by Synthesis?''. In Trends in Cognitive Neuroscience. Vol. 10. No. 7. 301-308. July. 2006.pubs\ucla\A203_ayuille_TICS2007.pdf

N. Chater, J. Tenenbaum, A.L. Yuille. "Probabilistic models of cognition: Where next?" In Trends in Cognitive Neurosciece. Vol. 10. No. 7. 292-293. July. 2006.pubs\ucla\A202_nchater_b_TICS2006.pdf

N. Chater, J. Tenenbaum and A.L. Yuille. ``Probabilistic Models of Cognition: Conceptual Foundations''. In Trends in Cognitive Neurosciece. Vol. 10. No. 7. 287-291. July. 2006.pubs\ucla\A201_nchater_a_TICS2006.pdf

B. Rokers, A.L. Yuille and Z. Liu. The perceived motion of a stereokinetic stimulus. Vision Research, 46(15):2375-87. July. 2006.pubs\ucla\A200_brokers_VISRES2006.pdf

I. Kokkinos, P. Maragos, A. L. Yuille: Bottom-Up & Top-down Object Detection using Primal Sketch Features and Graphical Models. CVPR (2) 2006: 1893-1900. 17-22 June. 2006.pubs\ucla\A199_ikokkinos_CVPR2006.pdf

H.J. Lu and A.L. Yuille. ``Ideal Observers for Detecting Human Motion: Correspondence Noise''. In Advances in Neural Information Processing Systems 18. Cambridge, MA: MIT Press. A Bradford Book. Eds. Y. Weiss, B. Schoelkopf and J. Platt. Pages 827-834. May 2006.pubs\ucla\A198_hjlu_ANIPS2006.pdf

A.L. Yuille: Augmented Rescorla-Wagner and Maximum Likelihood Estimation. In Advances in Neural Information Processing Systems18. Cambridge, MA: MIT Press. A Bradford Book. Eds. Y. Weiss, B. Schoelkopf and J. Platt. Pages 1561-1568. May 2006.pubs\ucla\A197_ayuille_ANIPS2006.pdf

L. Zhu, A.L. Yuille: A Hierarchical Compositional System for Rapid Object Detection. In Advances in Neural Information Processing Systems 18. Cambridge, MA: MIT Press. A Bradford Book. Eds. Y. Weiss, B. Schoelkopf and J. Platt. Pages 1633-1640. May 2006.pubs\ucla\A196_lzhu_ANIPS2006.pdf

2005

M. Rosen-Zvi, M. I. Jordan, A. L. Yuille: The DLR Hierarchy of Approximate Inference. UAI 2005: 493-500. 26-29 July. 2005.pubs\ucla\A194_mrosen-zvi_UAI2005.pdf

Z. Tu, X. Chen, A. L. Yuille, S-C Zhu: Image Parsing: Unifying Segmentation, Detection, and Recognition. International Journal of Computer Vision. (63), No. 2, pp. 113-140. July 2005.pubs\ucla\A193_ztu_IJCV2005.pdf

X. Chen and A.L. Yuille. . "A Time-Efficient Cascade for Real Time Object Detection". 1st International Workshop on Computer Vision Applications for the Visually Impaired. In association with CVPR 2005. San Diego. 20 June. 2005.pubs\ucla\A192_xchen_CVACVI2005.pdf

A.L. Yuille. ``The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters''. In Advances in Neural Information Processing Systems17. Cambridge, MA: MIT Press. A Bradford Book. Eds. L.K. Saul, Y. Weiss and L. Bottou. Pages 1585-1592. July 2005.pubs\ucla\A191_ayuille_ANIPS2005.pdf

A.L. Yuille. ``The Convergence of Contrastive Divergences''. In Advances in Neural Information Processing Systems 17. Cambridge, MA: MIT Press. A Bradford Book. Eds. L.K. Saul, Y. Weiss and L. Bottou. Pages 1593-1600. July 2005.pubs\ucla\A190_ayuille_cd_ANIPS2005.pdf

2004

D. Kersten, P. Mamassian and A.L. Yuille, “Object Perception as Bayesian Inference,” Annual Review of Psychology, 555, pp 271-304, 2004,pubs\ucla\A189_dkersten_ARP2004.pdf

X. Chen and A.L. Yuille, “AdaBoost Learning for Detecting and Reading Text in City Scenes,” In Proceedings Computer Vision and Pattern Recognition (CVPR), Vol. 2, pp 366-373, July 2004.pubs\ucla\A188_xchen_CVPR2004.pdf

A. Barbu and A.L. Yuille, “Motion Estimation by Swendsen-Wang Cuts,” In Proceedings Computer Vision and Pattern Recognition (CVPR), Vol. 1, pp 754-761, June 2004.pubs\ucla\A187_abarbu_CVPR2004.pdf

Z. Tu and A.L. Yuille, “Shape Matching and Recognition: Using Generative Models and Informative Features,” In Proceedings European Conference on Computer Vision. ECCV'04, Prague, Vol. 3, pp 195-209, May 2004,pubs\ucla\A186_ztu_ECCV2004.pdf

2003

J.M. Coughlan and A.L. Yuille, “A Large Deviation Theory Analysis of Bayesian Tree Search,” In Mathematical Methods in Computer Vision, Eds. P. Olver and A. Tannenbaum, IMA Volumes in Mathematics and its Applications, Vol. 133, pp 1-17, Spinger-Verlag New York Inc., 2003.pubs\ucla\A185_jmcoughlan_BOOKCHP2002.pdf

A.L. Yuille, Fang Fang, P. Schrater and D. Kersten, “Human and Ideal Observers for Detecting Image Curves,” In proceedings, Neural Infomration Processing Systems. NIPS, 2003. pubs\ucla\A184_ayuille_NIPS2003.pdf

A. Rangarajan, J.M. Coughlan and A.L. Yuille, “A Bayesian Network for Relational Shape Matching,” In Proceedings International Conference on Computer Vision ICCV'03, Nice, France, pp 671-678, October 2003.pubs\ucla\A183_arangarajan_ICCV2003.pdf

Z. Tu, X. Chen, A.L. Yuille and S.C. Zhu, “Image Parsing: Segmentation, Detection, and Recognition,” In Proceedings International Conference on Computer Vision ICCV'03, Nice, France, 18-25, October. 2003.pubs\ucla\A182_ztu_ICCV2003.pdf

D. Cremers and A.L. Yuille, “A Generative Model Based Approach to Motion Segmentation,” German Conf. on Pattern Recognition (DAGM), Magdeburg, Springer LNCS, Vol. 2781, September 2003, pp 313-320, B. Michaelis and G. Krell (Eds.),pubs\ucla\A181_dcremers_GCPR2003.pdf

A.L. Yuille, J.M. Coughlan, and S. Konishi, “The Generic Viewpoint Assumption and Planar Bias,” Pattern Analysis and Machine Intelligence, Vol. 25, No. 8, August 2003,pubs\ucla\A180_ayuille_PAMI2003.pdf

J.M. Coughlan and A.L. Yuille, “Manhattan World,” Neural Computation, Vol. 15, No. 5, May 2003, pp 1063-1088,pubs\ucla\A179_jcoughlan_NC2003.pdf

D. Kersten and A.L. Yuille, “Bayesian Models of Object Perception,” Current Opinion in Neurobiology, 13, April 2003, pp 1-9,pubs\ucla\A178_dkersten_CON2003.pdf

A.L. Yuille and Anand Rangarajan, “The Concave-Convex Procedure (CCCP),” Neural Computation, Vol. 15, No. 4, April 2003, pp 915-936.pubs\ucla\A177_ayuille_NC2003.pdf

S.M. Konishi, A.L. Yuille, and J.M. Coughlan, “A Statistical Approach to Multi-Scale Edge Detection,” Image and Vision Computing (IVC),” Special issue on Generative-Model Based Vision, Vol. 21, No. 1, January 2003, pp 37-48.pubs\ucla\A176_skonishi_IVC2003.pdf

J.M. Coughlan and A.L. Yuille, “Algorithms from Statistical Physics for Generative Models of Images,” Image and Vision Computing (IVC), Special issue on Generative-Model Based Vision, Vol. 21, No. 1, January 2003, pp 29-36,pubs\ucla\A175_jcoughlan_IVC2003.pdf

S. M. Konishi, A.L. Yuille, J.M. Coughlan and Song Chun Zhu, “Statistical Edge Detection: Learning and Evaluating Edge Cues,” Pattern Analysis and Machine Intelligence, Vol. 25, No. 1, January 2003, pp 57-74,pubs\ucla\A174_skonishi_PAMI2003.pdf

A.L. Yuille, J. M. Coughlan, and S. Konishi, “The KGBR Viewpoint-Lighting Ambiguity,” Journal of the American Optical Society A.(20), No. 1, January 2003, pp 24-31,pubs\ucla\A173_ayuille_JOSA2003.pdf

2002

"The KGBR Viewpoint-Lighting Ambiguity''. A.L. Yuille, J.M. Coughlan and S. Konishi. Journal of the Optical Society of America A. 2002. (file.ps.gz/file.pdf

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"CCCP Algorithms to Minimize the Bethe and Kikuchi Free Energies: Convergent Alternatives to Belief Propagation''. A.L. Yuille. Neural Computation.. Vol. 14. No. 7. pp 1691-1722. 2002.(file.ps.gz/file.pdf)

2001

"The KGBR Viewpoint-Lighting Ambiguity and its Resolution by Generic Constraints.'' A.L.Yuille, J.M. Coughlan and S. Konishi. Proceedings. ICCV'01. Vancouver, Canada. 2001. (file.ps.gz/file.pdf)

"The g Factor: Relating Distributions on Features to Distributions on Images''. J. M. Coughlan and A.L. Yuille. Proceedings NIPS'01. Vancouver, Canada. December. 2001.(file.ps.gz/file.pdf)

"Order Parameters for Minimax Entropy Distributions: When does high level knowledge help?' A.L. Yuille, J.M. Coughlan, Y-N. Wu and S.C. Zhu. International Journal of Computer Vision. 41(1/2), pp 9-33. 2001. (file.ps.gz/file.pdf)

"An Algorithm to Minimize the Bethe Free Energy''. A.L. Yuille. Proceedings EMMCVPR'01. Sophia-Antipolis. France. 2001.(file.ps.gz/file.pdf)

"The Concave-Convex Procedure (CCCP)''. A.L. Yuille and A. Rangarajan. Proceedings NIPS'00. 2001.(file.ps.gz/file.pdf)

"MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation". A. Rangarajan and A.L. Yuille. Procveedings NIPS'00. 2001. (file.ps.gz/file.pdf)

2000

"Probabilistic Motion estimation Based on Temporal Coherence". P-Y Burgi, A.L. Yuille, and N.M. Grzywacz. Neural Computation. Vol. 12. pp 1839-1867. 2000 (file.ps.gz/file.pdf)

"Statistical cues for Domain Specific Image Segmentation with Performance Analysis.'' S. M. Konishi and A.L. Yuille. Proccedings CVPR'2000. Hilton Head, South Carolina. 2000.(file.ps.gz/file.pdf)