Research of Ying Nian Wu
I am a statistician interested in statistical modeling and computing.
I am particularly interested in simple generative models that are cortex-like. The following are
two models I and my collaborators have crafted:
ACTIVE BASIS: the model learns to sketch
joint work with Song Chun Zhu and Zhangzhang Si et al.
FRAME: the model learns to paint
joint work with Song Chun Zhu and David Mumford et al.
PAPERS TO DOWNLOAD (list of publications)
YN Wu, Z Si, H Gong, SC Zhu (2010) Learning active basis model for object
detection and recognition. International Journal of Computer Vision,
90, 198-235.
pdf
reproducible
latex
ppt
Si, Z. and Wu, Y. N. (2010) Wavelet, active basis, and shape script
--- a tour in the sparse land. ACM SIGMM International Conference on
Multimedia Information Retrieval, Special session on Statistical Modeling and
Learning for Multimedia.
pdf
reproducible
latex
Z Si, H Gong, SC Zhu, YN Wu (2010) Learning active basis models by EM-type algorithms.
Statistical Science, 25, 458–475.
pdf
reproducible
latex
YN Wu, C Guo, SC Zhu (2008) From information scaling of natural images to
regimes of statistical models. Quarterly of Applied Mathematics, 66, 81-122.
pdf
latex
ppt
YN Wu, Z Si, C Fleming, and SC Zhu (2007) Deformable template as active basis.
Proceedings of International Conference of Computer Vision.
pdf
reproducible
latex
ppt
M Zheng, LO Barrera, B Ren, YN Wu (2007) ChIP-chip: data, model and analysis.
Biometrics, 63, 787-796.
pdf
source code
latex
ppt
C Guo, SC Zhu, and YN Wu (2007) Primal sketch: integrating structure
and texture. Computer Vision and Image Understanding, 106, 5-19.
pdf
source code
latex
ppt
C Guo, SC Zhu, and YN Wu (2003) Towards a mathematical theory of primal
sketch and sketchability. Proceedings of International Conference of Computer Vision.
1228-1235.
pdf
source code
latex
ppt
G Doretto, A Chiuso, YN Wu, S Soatto (2003) Dynamic textures. International
Journal of Computer Vision, 51, 91-109.
pdf (source
code given in paper)
results
YN Wu, SC Zhu (2001) Vision and the art of data augmentation. Discussion of a paper
by Meng and van Dyk. Journal of Computational and Graphical Statistics, 10, 90-93.
pdf
YN Wu, SC Zhu, X Liu (2000) Equivalence of Julesz ensembles and FRAME models.
International Journal of Computer Vision, 38, 247-265.
pdf
source code
JS Liu, YN Wu (1999) Parameter expansion for data augmentation. Journal of
the American Statistical Association, 94, 1264-1274.
pdf
C Liu, DB Rubin, YN Wu (1998) Parameter expansion to accelerate EM -- the PX-EM
algorithm. Biometrika, 85, 755-770.
pdf
SC Zhu, YN Wu, DB Mumford (1998) Minimax entropy principle and its application
to texture modeling. Neural Computation, 9, 1627-1660.
pdf
SC Zhu, YN Wu, DB Mumford (1997) Filter, Random field, And Maximum Entropy
(FRAME): towards a unified theory for texture modeling. International Journal
of Computer Vision, 27, 107-126.
pdf
YN Wu (1995) Random shuffling: a new approach to matching problem.
Proceedings of American Statistical Association, 69-74. Longer version
pdf