Stuart Geman

Q: What Schools Are Affiliated With Stuart Geman

Stuart Geman is affiliated with the following schools: Brown University, Rutgers University, Dartmouth College, Massachusetts Institute of Technology

Stuart Geman's AcademicInfluence.com Rankings

Stuart Geman

Mathematics

#2795

World Rank

#4239

Historical Rank

#1080

USA Rank

Measure Theory

#990

World Rank

#1284

Historical Rank

#368

USA Rank

mathematics Degrees

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Mathematics

Why Is Stuart Geman Influential?

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According to Wikipedia, Stuart Alan Geman is an American mathematician, known for influential contributions to computer vision, statistics, probability theory, machine learning, and the neurosciences. He and his brother, Donald Geman, are well known for proposing the Gibbs sampler, and for the first proof of convergence of the simulated annealing algorithm.

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Stuart Geman's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images (1984) (18958)
Neural Networks and the Bias/Variance Dilemma (1992) (3681)
Statistical methods for tomographic image reconstruction (1987) (669)
Boundary Detection by Constrained Optimization (1990) (581)
A Limit Theorem for the Norm of Random Matrices (1980) (452)
Nonparametric Maximum Likelihood Estimation by the Method of Sieves (1982) (394)
Diffusions for global optimizations (1986) (280)
Visual Turing test for computer vision systems (2015) (268)
Estimators for Stochastic "Unification-Based" Grammars (1999) (232)
Context and Hierarchy in a Probabilistic Image Model (2006) (208)
Markov Random Field Image Models and Their Applications to Computer Vision (2010) (191)
Estimation of Probabilistic Context-Free Grammars (1998) (126)
Compositionality, MDL Priors, and Object Recognition (1996) (117)
Conditional modeling and the jitter method of spike resampling. (2012) (111)
Hidden Markov Random Fields (1995) (81)
Spike Count Reliability and the Poisson Hypothesis (2006) (79)
At what time scale does the nervous system operate? (2003) (77)
Dynamic programming for parsing and estimation of stochastic unification-based grammars (2002) (76)
A Rate and History-Preserving Resampling Algorithm for Neural Spike Trains (2009) (74)
Consistent Cross-Validated Density Estimation (1983) (71)
THE SPECTRAL RADIUS OF LARGE RANDOM MATRICES (1986) (69)
SOME AVERAGING AND STABILITY RESULTS FOR RANDOM DIFFERENTIAL EQUATIONS (1979) (62)
Bayesian image restoration (1986) (61)
A nonlinear filter for film restoration and other problems in image processing (1992) (60)
Invariance and selectivity in the ventral visual pathway (2006) (45)
On the temporal resolution of neural activity (1998) (44)
Opinion: Science in the age of selfies (2016) (40)
Locating texture and object boundaries (1987) (37)
Dynamic programming and the graphical representation of error-correcting codes (2001) (36)
Bayesian Image Analysis (1986) (34)
Ambiguity and nonidentifiability in the statistical analysis of neural codes (2015) (31)
Neural Networks and the BiadVariance Dilemma (1992) (30)
Probability and statistics in computational linguistics, a brief review (2004) (27)
Almost Sure Stable Oscillations in a Large System of Randomly Coupled Equations (1982) (27)
Context, Computation, and Optimal ROC Performance in Hierarchical Models (2011) (24)
Computer simulation of brainstem respiratory activity. (1976) (22)
Stochastic Relaxation Methods for Image Restoration and Expert Systems (1988) (22)
A chaos hypothesis for some large systems of random equations (1982) (21)
Compositionality in neural systems (1998) (20)
Sieves for Nonparametric Estimation of Densities and Regressions. (1981) (15)
Probabilistic Grammars and their Applications (2015) (15)
Conditional Modeling and the Jitter Method of Spike Re-sampling: Supplement (2011) (12)
Image warping using radial basis functions (2010) (11)
Estimators for Stochastic \ Uni cation-Based " Grammars (1999) (10)
Dynamic programming, tree-width and computation on graphical models (2002) (10)
Invariance in the recurrence of large returns and the validation of models of price dynamics. (2013) (8)
On the Minimum Entropy of a Mixture of Unimodal and Symmetric Distributions (2008) (7)
Development of Laser Radar ATR Algorithms: Phase 2. Military Objects (1990) (6)
The statistical analysis of temporal resolution in the nervous system (2008) (5)
Maximum likelihood features for generative image models (2017) (5)
Grammatical approach to mine detection (1997) (5)
Empirical scaling laws and the aggregation of non-stationary data (2013) (5)
An Exact Jitter Method using Dynamic Programming (2004) (4)
Sparse feature selection by information theory (2014) (4)
Computer recognition of coronary arteries (1991) (3)
Where the adventure is (1995) (3)
On the Consistency of Minimum Complexity Nonparametric Estimation (1998) (3)
Dynamic programming algorithms for maximum likelihood decoding (1998) (3)
Using Statistics of Natural Images to Facilitate Automatic Receptive Field Analysis (2004) (3)
Statistical inference and probabilistic modeling in compositional vision (2009) (2)
[Neural Networks: A Review from Statistical Perspective]: Comment (1994) (2)
Transsacadic Information and Corollary Discharge in Local Field Potentials of Macaque V1 (2019) (2)
Base-pair ambiguity and the kinetics of RNA folding (2018) (1)
AD-A 237 544 Development of Laser iPadar ATR Algorithms : Phase II-Military Objects PHASE II TECHNICAL REPORT ' . . (1)
MAXIMUM LIKELIHOOD FEATURES FOR GENERATIVE IMAGE MODELS 1 (2017) (1)
Capacities and the Free Passage of Entropic Barriers. (2018) (0)
Nonparametric Estimation by the Method of Sieves. (1983) (0)
RESEARCH ARTICLE Image Warping Using Radial Basis Functions (2013) (0)
A Mathematical Framework for Image Analysis (1991) (0)
Estimation, Method of Sieves (2006) (0)
Primary and Supplementary Motor Areas Occur at Precise Spatiotemporal Repeating Patterns in Monkey (2015) (0)
Compositionality (0)
Parallel Algorithms for Maximum Entropy Calculation (1987) (0)
Base-pair ambiguity and the kinetics of RNA folding (2019) (0)
Cross-validation for densities and regressions (1982) (0)
Notes on a Spike Count Variability Test (2004) (0)
Associated With Distinct Action Segments Temporally Precise Cortical Firing Patterns Are (2015) (0)
Characterization of a maximum-likelihood nonparametric density estimator of kernel type (1982) (0)
Bayesian statistical methods applied to emission tomography with physical phantom and patient data (1992) (0)
Orchestrating Computation in Hierarchical Models (2011) (0)
Capacities and efficient computation of first-passage probabilities. (2020) (0)
Keynote Talk: Generative Hierarchical Models for Image Analysis (2009) (0)
Image Modeling: A Mathematical Framework for Segmentation and Object Detection. (1987) (0)
Probabilistic hierarchical image models (2006) (0)
Generative hierarchical models for image analysis (2009) (0)
Spiking Dynamics Analysis of Between-Trial and Within-Trial Neural (2015) (0)
Mathematical Foundations for Object Recognition and Image Analysis (2000) (0)
Overcoming Entropic Barriers by Capacity Hopping (2018) (0)
A Unified Mathematical Approach to Image Analysis. (1987) (0)
Mathematics of Sensing, Exploitation, and Execution (MSEE) Hierarchical Representations for the Evaluation of Sensed Data (2016) (0)

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Other Resources About Stuart Geman

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What Schools Are Affiliated With Stuart Geman?

Stuart Geman is affiliated with the following schools: