Please click here to view past research projects.
Probabilistic Models of Objects and Images
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This is a major focus of my research. It includes work on modeling
objects (A*, parsing, AAMs, unsupervised learning) with Iasonas Kokkinos.
Hierarchical inference algorithm with Jason Corso. Modeling
shape and hierarchical cues with Zhuowen Tu and SongFeng
Zheng. Work on text detection with X. (Alex) Chen, and work on
image parsing with Zhuowen Tu, Alex Chen and Song-Chun Zhu. |
Articles:
I. Kokkinos and A.L. Yuille 2009, I. Kokkinos and A.L. Yuille 2008,J. J. Corso, A.L. Yuille, and Z. Tu 2008, J. J. Corso, Z. Tu, and A.L. Yuille 2008,
Z. Tu, S.F. Zheng, and A.L. Yuille 2008, I. Kokkinos and A.L. Yuille 2007,
S.F. Zheng, Z. Tu, A. L. Yuille 2007, Z. Tu, X. Chen, A.L. Yuille and S.C. Zhu 2006,
I. Kokkinos, P. Maragos, A.L. Yuille 2006, Z. Tu, X. Chen, A.L. Yuille, S.C. Zhu 2005,
X. Chen and A.L. Yuille 2005, X. Chen and A.L. Yuille 2004,
Z. Tu and A.L. Yuille 2004, A. Rangarajan, J.M. Coughlan and A.L. Yuille 2003,
Z. Tu, X. Chen, A.L. Yuille and S.C. Zhu 2003
Compositional, Hierarchical and Recursive Models of Objects and Images
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This is the thesis work of Long (Leo) Zhu with several collaborators particularly Yuanhao Chen . This includes projects on unsupervised learning, structured machine learning techniques, compositional inference algorithms, and hierarchical representations. |
Articles:
Y. Chen, L. Zhu, A. L. Yuille, H. Zhang 2009, L. Zhu, Y. Chen, A.L. Yuille 2009a,L. Zhu, Y. Chen, A.L. Yuille 2009b, L. Zhu, Y. Chen, Y. Lin, C. Lin, A.L. Yuille 2008,
L. Zhu, C. Lin, H. Huang, Y. Chen, A.L. Yuille 2008, Y. Chen, L. Zhu, A.L. Yuille, H. Zhang 2008,
L. Zhu, Y. Chen, X. Ye, A.L. Yuille 2008, L. Zhu, Y. Chen, Y. Lu, C.Lin, A.L. Yuille 2008,
L. Zhu, Y. Chen, C. Lin, A.L. Yuille 2007, L. Zhu, Y. Chen, and A.L. Yuille 2006,
L. Zhu, A.L. Yuille 2005
Computational Modeling of Human Motion Perception
Current topics include developing hierarchical models of visual motion perception and testing them with psychophysics experiments and comparison to physiological data. This work involves Xuming He, Shuang Wu, and HongJing Lu. Some related work was done with Zili Liu and Bas Rokers. I organized a workshop and edited proceedings with Dan Cremers and Bodo Rosenhahn on Statistical and Geometric Approaches to Visual Motion Analysis.Articles:
S. Wu, H.J. Lu, A. Lee and A.L. Yuille 2009, S. Wu, H.J. Lu, A.L. Yuille 2008,B. Rokers, A.L. Yuille and Z. Liu 2006, H.J. Lu and A.L. Yuille 2005,
A. Barbu and A.L. Yuille 2004, D. Cremers and A.L. Yuille 2003
Computational Models of Cognition
This research aims to develop computational models of the cognitive abilities of humans, and animals. Cognition is modeled as probabilistic inference over structure representations. This is part of a broader research program and has lead to an IPAM workshop and an IPAM summer school co-organized with Josh Tenenbaum. The IPAM summer school webpages contain videos and pdf's of three weeks of lectures.Current projects are on causal and analogical learning and reasoning (with Randall Rojas and Matt Weiden). These projects are performed with collaborators in the Psychology Department – such as HongJing Lu, Keith Holyoak, and Patricia Cheng. Some of this work motivates new models and methods for machine learning with HongJing Lu and SongFeng Zheng. Earlier work (by myself) analyzed the convergence properties of the Rescorla-Wagner algorithms and its relations to probabilistic inference.
Articles:
HJ Lu, M. Weiden, and A.L. Yuille 2009, A.L. Yuille and S.F. Zheng 2009,H.J. Lu, A.L. Yuille, M. Liljeholm, P.W. Cheng, and K.J. Holyoak 2008,
H.J. Lu, R. Rojas, T. Beckers, and A.L. Yuille 2008, T.L. Griffiths and A.L. Yuille 2008,
A.L. Yuille and H.J. Lu 2007, H.J. Lu, A.L Yuille, M. Liljeholm, P.W. Cheng, and K.J. Holyoak 2007,
H.J. Lu, A.L Yuille, M. Liljeholm, P.W. Cheng, and K.J. Holyoak 2006, T.L. Griffiths and A.L. Yuille 2006,
N. Chater, J. Tenenbaum, A.L. Yuille 2006, N. Chater, J. Tenenbaum and A.L. Yuille 2006,
A.L. Yuille 2005, A.L. Yuille 2004.
Machine Learning analysis of fMRI data
My work on these topics is in collaboration with Mark Cohen and Ariana Anderson. It uses machine learning methods – e.g., ICA, random forests, SVM – for diagnosis and classification/regression of mental states from fMRI observations.Articles:
Anderson, Dinov, Sherin, Quintana, Yuille and Cohen 2009Medical Image Interpretation
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I collaborated with Zhuowen Tu and Jason Corso (now U. Buffalo) on methods for automatically segmenting brains and detecting tumors and other pathological structures. |
Articles:
J. J. Corso, E. Sharon, S. Dube, S. El-Saden, U. Sinha, and A.L. Yuille 2008,J. Corso, A.L. Yuille, N. Sicotte, and A. Toga 2007, J. J. Corso, Z. Tu, A. Yuille, and A.W. Toga 2007,
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 2007, J. J. Corso, E. Sharon, and A. L. Yuille 2006,
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 2006.
Computational Models of the Visual Cortex
Research with Daniel Kersten and Tai Sing Lee.Articles:
T.S. Lee and A.L. Yuille 2007, A.L. Yuille and D. Kersten 2006,D. Kersten, P. Mamassian and A.L. Yuille 2004, D. Kersten and A.L. Yuille 2003.