Research of Ying Nian Wu

I am interested in statistical modeling, computing and learning. In particular, I am interested in generative models and unsupervised learning.

SELECTED PAPERS TO DOWNLOAD (list of publications)

J Xie*, Z Zheng*, R Gao, W Wang, SC Zhu, and YN Wu (2018) Learning descriptor networks for 3D shape synthesis and analysis. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pdf project page (* equal contributions)

R Gao*, Y Lu*, J Zhou, SC Zhu, and YN Wu (2018) Learning generative ConvNets via multigrid modeling and sampling. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pdf project page (* equal contributions)

J Xie, Y Lu, R Gao, and YN Wu (2018) Cooperative learning of energy-based model and latent variable model via MCMC teaching. AAAI-18: 32nd AAAI Conference on Artificial Intelligence. pdf slides project page

J Xie, SC Zhu, and YN Wu (2017) Synthesizing dynamic patterns by spatial-temporal generative ConvNet. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pdf project page

T Han*, Y Lu*, SC Zhu, and YN Wu (2017) Alternating Back-Propagation for Generator Network. AAAI-17: 31st AAAI Conference on Artificial Intelligence. pdf project page (* equal contributions)

J Xie*, Y Lu*, SC Zhu, and YN Wu (2016) A Theory of Generative ConvNet. International Conference on Machine Learning. pdf project page (* equal contributions)

Y Lu, SC Zhu, and YN Wu (2016) Learning FRAME models using CNN filters. AAAI-16: 30th AAAI Conference on Artificial Intelligence. pdf project page

J Xie, Y Lu, SC Zhu, and YN Wu (2016) Inducing wavelets into random fields via generative boosting. Applied and Computational Harmonic Analysis, 41, 4-25. pdf project page

J Dai, Y Lu, and YN Wu (2015) Generative modeling of convolutional neural networks. International Conference on Learning Representations. pdf project page

J Xie, W Hu, SC Zhu, and YN Wu (2014) Learning sparse FRAME models for natural image patterns. International Journal of Computer Vision. pdf project page

J Dai, Y Hong, W Hu, SC Zhu, and YN Wu (2014) Unsupervised learning of dictionaries of hierarchical compositional models. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pdf project page

J Dai, YN Wu, J Zhou, and SC Zhu (2013) Cosegmentation and cosketch by unsupervised learning. Proceedings of International Conference on Computer Vision (ICCV). pdf project page

Y Hong, Z Si, WZ Hu, SC Zhu, and YN Wu (2013) Unsupervised learning of compositional sparse code for natural image representation. Quarterly of Applied Mathematics. pdf project page

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 project page

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 project page

Z Si, H Gong, SC Zhu, YN Wu (2010) Learning active basis models by EM-type algorithms. Statistical Science, 25, 458-475. pdf project page

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

YN Wu, Z Si, C Fleming, and SC Zhu (2007) Deformable template as active basis. Proceedings of International Conference of Computer Vision. pdf project page

M Zheng, LO Barrera, B Ren, YN Wu (2007) ChIP-chip: data, model and analysis. Biometrics, 63, 787-796. pdf

C Guo, SC Zhu, and YN Wu (2007) Primal sketch: integrating structure and texture. Computer Vision and Image Understanding, 106, 5-19. pdf project page

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 project page

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) project page

YN Wu, SC Zhu, X Liu (2000) Equivalence of Julesz ensembles and FRAME models. International Journal of Computer Vision, 38, 247-265. pdf project page

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