• Publications
  • Influence
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
  • S. Geman, D. Geman
  • Mathematics, Computer Science
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 November 1984
TLDR
We make an analogy between images and statistical mechanics systems. Expand
  • 12,173
  • 503
  • PDF
Stochastic relaxation, Gibbs distrib. Bayesian restoration of img
  • 2,131
  • 224
Neural Networks and the Bias/Variance Dilemma
TLDR
We present a tutorial on nonparametric inference and its relation to neural networks, and we use the statistical viewpoint to highlight strengths and weaknesses of neural models. Expand
  • 3,174
  • 104
  • PDF
Boundary Detection by Constrained Optimization
TLDR
A statistical framework is used for finding boundaries and for partitioning scenes into homogeneous regions. Expand
  • 561
  • 39
  • PDF
Statistical methods for tomographic image reconstruction
  • 600
  • 38
A Limit Theorem for the Norm of Random Matrices
  • 395
  • 33
Nonparametric Maximum Likelihood Estimation by the Method of Sieves
Maximum likelihood estimation often fails when the parameter takes values in an infinite dimensional space. For example, the maximum likelihood method cannot be applied to the completelyExpand
  • 338
  • 27
  • PDF
Estimators for Stochastic "Unification-Based" Grammars
TLDR
Log-linear models provide a statistically sound framework for Stochastic "Unification-Based" Grammars (SUBGs) and stochastic versions of other kinds of grammars. Expand
  • 227
  • 25
  • PDF
Diffusions for global optimizations
We seek a global minimum of $U:[0,1]^n \to R$. The solution to $({d / {dt}})x_t = - \nabla U(x_t )$ will find local minima. The solution to $dx_t = - \nabla U(x_t )dt + \sqrt {2T} dw_t $, where w isExpand
  • 292
  • 15