| 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 | 28465 | 1984 |
| 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 | 2205 | 2010 |
| Shape quantization and recognition with randomized trees Y Amit, D Geman Neural computation 9 (7), 1545-1588, 1997 | 1836 | 1997 |
| Constrained restoration and the recovery of discontinuities D Geman, G Reynolds IEEE Transactions on Pattern Analysis & Machine Intelligence 14 (03), 367-383, 1992 | 1612 | 1992 |
| Nonlinear image recovery with half-quadratic regularization D Geman, C Yang IEEE transactions on Image Processing 4 (7), 932-946, 1995 | 1240 | 1995 |
| Bayesian image analysis D Geman, S Geman Disordered systems and biological organization, 301-319, 1986 | 736 | 1986 |
| 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 | 728 | 1990 |
| 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 | 727 | 1996 |
| Occupation densities D Geman, J Horowitz The Annals of Probability, 1-67, 1980 | 610 | 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 | 480 | 2005 |
| 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 (1), 2004 | 422 | 2004 |
| Random fields and inverse problems in imaging A Ancona, D Geman, N Ikeda, D Geman Ecole d'ete de Probabilites de Saint-Flour XVIII-1988, 115-193, 1990 | 416 | 1990 |
| Coarse-to-fine face detection F Fleuret, D Geman International Journal of computer vision 41, 85-107, 2001 | 399 | 2001 |
| 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 | 398 | 2015 |
| 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 | 316 | 2005 |
| 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 | 295 | 1984 |
| 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 | 291 | 1997 |
| Théorie du potentiel sur les graphes et les variétés A Ancona, D Geman, N Ikeda, A Ancona École d'été de Probabilités de Saint-Flour XVIII-1988, 3-112, 1990 | 264 | 1990 |
| A computational model for visual selection Y Amit, D Geman Neural computation 11 (7), 1691-1715, 1999 | 250 | 1999 |
| Computational medicine: translating models to clinical care RL Winslow, N Trayanova, D Geman, MI Miller Science translational medicine 4 (158), 158rv11-158rv11, 2012 | 228 | 2012 |
