| Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images S Geman, D Geman IEEE Transactions on pattern analysis and machine intelligence, 721-741, 1984 | 24614 | 1984 |
| Constrained restoration and the recovery of discontinuities D Geman, G Reynolds IEEE Transactions on pattern analysis and machine intelligence 14 (3), 367-383, 1992 | 1458 | 1992 |
| Tackling the widespread and critical impact of batch effects in high-throughput data JT Leek, RB Scharpf, HC Bravo, D Simcha, B Langmead, WE Johnson, ... Nature Reviews Genetics 11 (10), 733-739, 2010 | 1443 | 2010 |
| Shape quantization and recognition with randomized trees Y Amit, D Geman Neural computation 9 (7), 1545-1588, 1997 | 1313 | 1997 |
| Nonlinear image recovery with half-quadratic regularization D Geman, C Yang IEEE transactions on Image Processing 4 (7), 932-946, 1995 | 951 | 1995 |
| Fundamentals of stochastic filtering A Bain, D Crisan Springer Science & Business Media, 2008 | 701 | 2008 |
| An active testing model for tracking roads in satellite images D Geman, B Jedynak IEEE Transactions on Pattern Analysis and Machine Intelligence 18 (1), 1-14, 1996 | 684 | 1996 |
| Boundary detection by constrained optimization D Geman, S Geman, C Graffigne, P Dong IEEE Transactions on pattern analysis and machine intelligence 12 (7), 609-628, 1990 | 671 | 1990 |
| Occupation densities D Geman, J Horowitz The Annals of Probability, 1-67, 1980 | 517 | 1980 |
| Simple decision rules for classifying human cancers from gene expression profiles AC Tan, DQ Naiman, L Xu, RL Winslow, D Geman Bioinformatics 21 (20), 3896-3904, 2005 | 407 | 2005 |
| Random fields and inverse problems in imaging D Geman École d'été de probabilités de Saint-Flour XVIII-1988, 115-193, 1990 | 371 | 1990 |
| Coarse-to-fine face detection F Fleuret, D Geman International Journal of computer vision 41 (1), 85-107, 2001 | 358 | 2001 |
| Classifying gene expression profiles from pairwise mRNA comparisons D Geman, C d'Avignon, DQ Naiman, RL Winslow Statistical applications in genetics and molecular biology 3, Article19, 2004 | 348 | 2004 |
| Bayes smoothing algorithms for segmentation of binary images modeled by Markov random fields H Derin, H Elliott, R Cristi, D Geman IEEE Transactions on Pattern Analysis and Machine Intelligence, 707-720, 1984 | 267 | 1984 |
| Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach. L Wolf, A Shashua, D Geman Journal of Machine Learning Research 6 (11), 2005 | 262 | 2005 |
| Joint induction of shape features and tree classifiers Y Amit, D Geman, K Wilder IEEE transactions on pattern analysis and machine intelligence 19 (11), 1300 …, 1997 | 253 | 1997 |
| Visual turing test for computer vision systems D Geman, S Geman, N Hallonquist, L Younes Proceedings of the National Academy of Sciences 112 (12), 3618-3623, 2015 | 248 | 2015 |
| A computational model for visual selection Y Amit, D Geman Neural computation 11 (7), 1691-1715, 1999 | 238 | 1999 |
| A coarse-to-fine strategy for multiclass shape detection Y Amit, D Geman, X Fan IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (12), 1606 …, 2004 | 171 | 2004 |
| Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data L Xu, AC Tan, DQ Naiman, D Geman, RL Winslow Bioinformatics 21 (20), 3905-3911, 2005 | 163 | 2005 |
