Final thesis for the fulfilment of the requirements for the degree of MSc. in Applied Computing Science Improving Score Matching for learning statistical models of natural images

[1]  Aapo Hyvärinen,et al.  Estimating Markov Random Field Potentials for Natural Images , 2009, ICA.

[2]  Michael J. Black,et al.  Fields of Experts , 2009, International Journal of Computer Vision.

[3]  Aapo Hyvärinen,et al.  Optimal Approximation of Signal Priors , 2008, Neural Computation.

[4]  Tijmen Tieleman,et al.  Training restricted Boltzmann machines using approximations to the likelihood gradient , 2008, ICML '08.

[5]  Marc'Aurelio Ranzato,et al.  Sparse Feature Learning for Deep Belief Networks , 2007, NIPS.

[6]  Aapo Hyvärinen,et al.  A Two-Layer ICA-Like Model Estimated by Score Matching , 2007, ICANN.

[7]  Aapo Hyvärinen,et al.  Connections Between Score Matching, Contrastive Divergence, and Pseudolikelihood for Continuous-Valued Variables , 2007, IEEE Transactions on Neural Networks.

[8]  William T. Freeman,et al.  What makes a good model of natural images? , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Aapo Hyvärinen,et al.  Some extensions of score matching , 2007, Comput. Stat. Data Anal..

[10]  Eero P. Simoncelli,et al.  Statistical Modeling of Images with Fields of Gaussian Scale Mixtures , 2006, NIPS.

[11]  Michael J. Black,et al.  Denoising Archival Films using a Learned Bayesian Model , 2006, 2006 International Conference on Image Processing.

[12]  Geoffrey E. Hinton,et al.  Reducing the Dimensionality of Data with Neural Networks , 2006, Science.

[13]  Yee Whye Teh,et al.  Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation , 2006, Cogn. Sci..

[14]  Charles Kervrann,et al.  Unsupervised Patch-Based Image Regularization and Representation , 2006, ECCV.

[15]  Fu Jie Huang,et al.  A Tutorial on Energy-Based Learning , 2006 .

[16]  Peter V. Gehler,et al.  Products of Edge-perts , 2005, NIPS.

[17]  Aapo Hyvärinen,et al.  Estimation of Non-Normalized Statistical Models by Score Matching , 2005, J. Mach. Learn. Res..

[18]  Michael J. Black,et al.  Fields of Experts: a framework for learning image priors , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[19]  Jean-Michel Morel,et al.  A Review of Image Denoising Algorithms, with a New One , 2005, Multiscale Model. Simul..

[20]  Geoffrey E. Hinton,et al.  Exponential Family Harmoniums with an Application to Information Retrieval , 2004, NIPS.

[21]  Geoffrey E. Hinton Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.

[22]  Eero P. Simoncelli,et al.  Image Denoising using Gaussian Scale Mixtures in the Wavelet Domain , 2002 .

[23]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[24]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[25]  Edward E. Smith,et al.  An Invitation to cognitive science , 1997 .

[26]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.

[27]  Song-Chun Zhu,et al.  Prior Learning and Gibbs Reaction-Diffusion , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Joachim Weickert,et al.  A Review of Nonlinear Diffusion Filtering , 1997, Scale-Space.

[29]  Terrence J. Sejnowski,et al.  Edges are the Independent Components of Natural Scenes , 1996, NIPS.

[30]  Jürgen Schmidhuber,et al.  Semilinear Predictability Minimization Produces Well-Known Feature Detectors , 1996, Neural Computation.

[31]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[32]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[33]  S. Mitter,et al.  On sampling methods and annealing algorithms , 1990 .

[34]  Lawrence D. Jackel,et al.  Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.

[35]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[36]  George M. Siouris,et al.  Applied Optimal Control: Optimization, Estimation, and Control , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[37]  Julius. Nelson A Study of Dreams , 1888 .