2023

• A Chattopadhyay, BD Haeffele, R Vidal, D Geman, "Performance Bounds for Active Binary Testing with Information Maximization" 2023/10/13 (pdf)
• Min Wang, Peter B Barker, Nicola G Cascella, Jennifer M Coughlin, Gerald Nestadt, Frederick C Nucifora Jr, Thomas W Sedlak, Alexandra Kelly, Laurent Younes, Donald Geman, Lena Palaniyappan, Akira Sawa, Kun Yang, "Longitudinal changes in brain metabolites in healthy controls and patients with first episode psychosis: a 7-Tesla MRS study" Molecular psychiatry 28 (5), 2018-2029 (link)
• Mohamed Omar, Wikum Dinalankara, Lotte Mulder, Tendai Coady, Claudio Zanettini, Eddie Luidy Imada, Laurent Younes, Donald Geman, Luigi Marchionni, "Using biological constraints to improve prediction in precision oncology" Iscience 26 (3) (pdf)
• Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin D Haeffele, Donald Geman, René VidalVariational information pursuit for interpretable predictions arXiv preprint arXiv:2302.02876 (pdf)
• Lanlan Ji, An Wang, Shreyash Sonthalia, Daniel Q Naiman, Laurent Younes, Carlo Colantuoni, Donald Geman, "CellCover Defines Conserved Cell Types and Temporal Progression in scRNA-seq Data across Mammalian Neocortical Development" bioRxiv, 2023.04. 06.535943 (pdf)

2022

• Aditya Chattopadhyay, Stewart Slocum, Benjamin D Haeffele, Rene Vidal, Donald Geman, "Interpretable by design: Learning predictors by composing interpretable queries" IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7430-7443 (pdf)
• Kun Yang, Koko Ishizuka, Zui Narita, Yukiko Y Lema, Siwei Zhang, Jubao Duan, L Younes, D Geman, A Lane, A Sawa, "Olfactory neuronal cells: biopsied surrogates for neurons in the brain" 2022 bioRxiv Pages 509290 (pdf

2021

• Q Ke, W Dinalankara, L Younes, D Geman, L Marchionni, "Efficient representations of tumor diversity with paired DNA-RNA aberrations" PLoS computational biology 17 (6), e1008944 (link
• W Dinalankara, Q Ke, D Geman, L Marchionni, "An R package for divergence analysis of omics data" PloS one 16 (4), e0249002 (link)
• Yuchun Fang, Zhengye Xiao, Wei Zhang, Yan Huang, Liang Wang, Nozha Boujemaa, Donald Geman, "Attribute prototype learning for interactive face retrieval" 2021/2/12nIEEE Transactions on Information Forensics and Security Volume 16 Pages 2593-2607
• Neil Hallonquist, Donald German, Laurent Younes, "Graph Discovery for Visual Test Generation" 2021/1/10 2020 25th International Conference on Pattern Recognition (ICPR) Pages 7500-7507 (pdf)

2020

• Priyanka Baloni, Wikum Dinalankara, John C Earls, Theo A Knijnenburg, Donald Geman, Luigi Marchionni, Nathan D Price, "Identifying personalized metabolic signatures in breast cancer" 2020/12/30 Metabolites Volume 11 Issue 1 Pages 20 (link)
• Aditya Chattopadhyay, Benjamin David Haeffele, Donald Geman, Rene Vidal, "Quantifying task complexity through generalized information measures" 2020/10/2 (pdf)
• Min Wang, Peter B Barker, Nicola Cascella, Jennifer M Coughlin, Gerald Nestadt, Frederick C Nucifora, Thomas W Sedlak, Alexandra Kelly, Laurent Younes, Donald Geman, Akira Sawa, Kun Yang, "Longitudinal changes in brain metabolites in healthy subjects and patients with first episode psychosis (FEP): a 7-Tesla MRS study" bioRxiv 2020/8/26 Pages 2020.08. 25.267419 (pdf)
• Qian Ke, Wikum Dinalankara, Laurent Younes, Donald Geman, Luigi Marchionni, "Efficient Representations of Tumor Diversity with Paired DNA-RNA Anomalies" bioRxiv 2020/6/1 (pdf)
• Kamel Lahouel, Laurent Younes, Ludmila Danilova, Francis M Giardiello, Ralph H Hruban, John Groopman, Kenneth W Kinzler, Bert Vogelstein, Donald Geman, Cristian Tomasetti, "Revisiting the tumorigenesis timeline with a data-driven generative model" Proceedings of the National Academy of Sciences 117 (2), 857-864
• P Baloni, W Dinalankara, JC Earls, TA Knijnenburg, D Geman, L Marchionni, ND Price, "Identifying Personalized Metabolic Signatures in Breast Cancer. Metabolites" 2021, 11, 20 (pdf)

2019

• W. Dinalankara, Q. Ke, D. Geman and L. Marchionni, "Divergence: An R Package for Divergence Analysis of Omics Data," bioRxiv, 2019
• K. Lahouel, D. Geman and L. Younes, "Coarse-to-fine multiple testing strategies", Electronic Journal of Statistics, 2019 (pdf)

2018

• W. Dinalankara, Q. Ke, Y. Xu, L. Ji, N. Pagane, A. Lien, T. Matam, E.J. Fertig, N. Price, L. Younes, L. Marchionni and D. Geman, "Digitizing omics profiles by divergence from a baseline", PNAS, 2018 (pdf)
• P. Slama, M. R. Hoopmann, R. L. Moritz and D. Geman, "Robust determination of differential abundance in shotgun proteomics using nonparametric statistics", Molecular Omics, 2018 (pdf)
• B. Afsari, T. Guo, M. Considine, L. Florea, L. T. Kagohara, G. L. Stein-O'Brien, D. Kelley, E. Flam, K. D. Zambo, P. K. Ha, D. Geman, M. F. Ochs, J. A. Califano, D. A. Gaykalova, A. V. Favorov and E. J. Fertig, "Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer", Bioinformatics, 2018 (pdf)

2017

• S. Ament, J. Pearl, A. Grindeland, J. St Claire, J. Earls, M. Kovalenko, T. Gillis, J. Mysore, J. Gusella, et al, "High resolution time-course mapping of early transcriptomic, molecular and cellular phenotypes in Huntington's disease CAG knock-in mice across multiple genetic backgrounds," Human Molecular Genetics, 2017 (pdf)

2016

• D. Geman and S. Geman, "Science in the age of selfies", PNAS, 2016 (pdf)

2015

• L. Chang and D. Geman, "Tracking Cross-Validated Estimates of Prediction Error as Studies Accumulate", Journal of the American Statistical Association, 2015 (pdf)
• D. Geman, S. Geman, N. Hallonquist and L. Younes, "Visual Turing test for computer vision systems", PNAS, 2015 (pdf)
• D. Geman, H. Geman, and N. N. Taleb, "Tail Risk Constraints and Maximum Entropy", Entropy, 2015 (pdf)
• D.Geman, M.Ochs, N.D. Price, C. Tomasetti, and L. Younes, "An argument for mechanism-based statistical inference in cancer", Human Genetics, DOI 10.1007/s00439-014-1501-x, 2014. (pdf)
• A. Rejeb-Sfar, N. Boujemaa and D. Geman, "Confidence sets for fine-grained categorization and plant identification", IJCV, DOI 10.1007/s11263-014-0743-3, 2014. (pdf)

2014

• S. Ma, J. Sung, A. T. Magis, Y. Wang, D. Geman and N.D. Price, "Measuring the effect of inter-study variability on estimating prediction error", PLOS ONE, 9, 2014. (pdf)
• B. Afsari, U. Braga-Neto and D. Geman, "Rank discriminants for predicting phenotypes from RNA expression", Annals of Applied Statistics, 8, 1469-1491, 2014. (pdf)
• B. Afsari, E.J. Fertig, D. Geman and L. Marchionni, "switchBox: An R package for k-Top Scoring Pairs (kTSP) classifier development", Bioinformatics, September, 2014. (pdf)
• B. Afsari, D. Geman and E.J. Fertig, "Learning dysregulated pathways in cancers from differential variability analysis", Cancer Informatics, 13, 62-67, 2014. (pdf)

2013

• A. Rejeb-Sfar, N. Boujemaa, D. Geman, "Vantage feature frames for fine-grained categorization," CVPR 2013 (pdf)
• D. Simcha, L. Younes, M, Aryee and D. Geman, "Identification of direction in gene networks from expression and methylation." BMC Systems Biology 7:118, 2013 (pdf)
• J. Sung, P-J Kim, C. Funk, S. Ma, A. Magis, Y. Wang, L. Hood, D. Geman and N.D. Price, "Multi-study integration of brain cancer transcriptomes reveals organ-level diagnostic signatures," PLOS Computational Biology, Vol 9, Issue 7, e1003148, 2013 (pdf)
• L. Marchionni, B. Afsari, D. Geman and J.T.Leek, "A simple and reproducible breast cancer prognostic test," BMC Genomics 14:336, 2013. (pdf)
• F. Sanchez-Vega, J. Eisner, L. Younes and D. Geman, "Learning multivariate distributions by competitive assembly of marginals," IEEE Transactions on Pattern Analysis and Machine Intelligence 35, 398-410, 2013. (pdf)

2012

• R.L. Winslow, N. Trayanova, D. Geman and M.I. Miller, "Computational medicine: translating models to clinical care," Science Translational Medicine 4, 31 October 2012 (pdf)
• F. Sanchez-Vega, J. Eisner, L. Younes and D. Geman, "Learning multivariate distributions by competitive assembly of marginals,"IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 (pdf)
• Simcha D, Price ND, Geman D, "The Limits of De Novo DNA Motif Discovery,"PLoS ONE 7(11): e47836 (pdf)

2011

• F. Fleuret, T. Li, C. Dubout, E. K. Wampler, S. Yantis and D. Geman, "Comparing machines and humans on a visual categorization test," PNAS, 108: 17621-17625, 2011. (pdf)
• R. L. Winslow et al., "The CardioVascular Research Grid Project." In: AMIA 2011 Summit on Translational Bioinformatics, March 7-9, San Francisco, CA, 77-81, 2011. (pdf)
• E. Yoruk, M. Ochs, D. Geman and L. Younes, "A comprehensive statistical model for cell signaling," IEEE Trans. Computational Biology and Bioinformatics , 592-606, 2011. (pdf)

2010

• P. Slama and D. Geman, "Identification of family-determining residues in PHD fingers," Nucleic Acids Research , 1-14, 2010. (pdf)
• J.T. Leek, R.B. Scharpf, H.C. Bravo, D. Simcha, B. Langmead, W.E. Johnson, D. Geman, K. Baggerly, R.A. Irisarry, "Tackling the widespread and critical impact of batch effects in high-throughput data," Nature Reviews Genetics , 11, 733-739, 2010. (pdf)
• J.A. Eddy, L. Hood, N.D. Price and D. Geman, "Identifying tightly regulated and variably expressed networks by differential rank conservation," PLoS Computational Biology , 2010. (pdf)
• J.A. Eddy, J. Sung, D. Geman and N.D. Price, "Relative expression analysis for molecular diagnosis and prognosis," Technology in Cancer Research and Treatment 9, 149-159, 2010. (pdf)

2009

• L.B. Edelman, G. Goia, D. Geman,, W. Zhang and N.D. Price, "Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases," BMC Genomics 10:583, 2009. (pdf)
• X. Lin, B. Afsari, L. Marchionni, L. Cope, G. Parmigiani, D. Naiman and D. Geman, "The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations," BMC Bioinformatics 10:256, 2009. (pdf)
• M. Ferecatu and D. Geman, "A statistical framework for image category search from a mental picture," IEEE Trans. PAMI, 31, 1087-1101, 2009. (pdf)

2008

• D. Geman, B. Afsari, A.C. Tan and D. Naiman "Microarray classification from several two-gene experssion comparisons," Proceedings ICMLA, 2008 (Winner, ICMLA Microarray Classification Algorithm Competition). (pdf)
• F. Fleuret and D. Geman, "Stationary features and cat detection," Journal of Machine Learning Research, 9:2549-2578, 2008. (pdf)
• L. Xu, A.C. Tan, R. L. Winslow and D. Geman, "Merging microarray data from separate breast cancer studies provides a robust prognostic signature," BMC Bioinformatics 9:125, 2008. (pdf)

2007

• M. Ferecatu and D. Geman, "Interactive search for image categories by mental matching," Proceedings Inter. Conf. on Computer Vision (ICCV '07) , Rio de Janeiro, October 14-20, 2007. (pdf)
• T.J. Anderson, I. Tchernyshyov, R. Diez, R.N. Cole, D. Geman, C.V. Dang and R. Winslow, "Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data," Proteomics 7: 1197-1207, 2007. (pdf)
• L. Xu, D. Geman and R. Winslow, "Large-scale integration of cancer microarray data identifies a robust common cancer signature," BMC Bioinformatics 8:275, 2007. (pdf)

2006

• S. Gangaputra and D. Geman, "A design principle for coarse-to-fine classification," Proceedings CVPR 2006, 2, 1877-1884, 2006. (pdf)
• A. Koloydenko and D. Geman, "Ordinal coding of image microstructure," Proceedings Inter. Conf. Image Processing, Computer Vision and Pattern Recognition (IPCV'06), Las Vegas, NV, June, 2006. (pdf)
• S. Gangaputra and D. Geman, "The trace model for object detection and tracking," Toward Category-Level Object Recognition (eds. J. Ponce et al), Lecture Notes in Computer Science, 4170, 401-420, 2006. (pdf)
• H. Sahbi and D. Geman, "A hierarchy of support vector machines for pattern detection," Journal of Machine Learning Research, 7, 2087-2123, 2006. (pdf)

2005

• L. Xu, A-C Tan, D. Naiman, D. Geman and R. Winslow, "Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data," Bioinformatics , 21, 3905-3911, 2005. (pdf)
• A-C Tan, D. Naiman, L. Xu, R. Winslow and D. Geman, "Simple decision rules for classifying human cancers from gene expression profiles," Bioinformatics , 21, 3896-3904, 2005. (pdf)
• Y. Fang and D. Geman, "Experiments in mental face retrieval," Proceedings AVBPA 2005, Lecture Notes in Computer Science, 637-646, July 2005. (Best Student Paper Award) (pdf)
• S. Gangaputra and D. Geman, "A unified stochastic model for detecting and tracking faces," Proceedings Second Canadian Conf. on Computer and Robot Vision (CRV'05), 306-313, 2005. (pdf)
• G. Blanchard and D. Geman, "Sequential testing designs for pattern recognition," Annals of Statistics, 33, 1155-1202, June, 2005. (pdf)

2004

• D. Geman, C. d'Avignon, D. Naiman, R. Winslow and A. Zeboulon, "Gene expression comparisons for class prediction in cancer studies," Proceedings 36'th Symposium on the Interface: Computing Science and Statistics, 2004. (pdf)
• Y. Amit, D. Geman and X. Fan, "A coarse-to-fine strategy for multi-class shape detection,"  IEEE Trans. PAMI, 28, 1606-1621,  2004. (pdf)
• D. Geman, C. d'Avignon, D. Naiman and R. Winslow, "Classifying gene expression profiles from pairwise mRNA comparisons," Statist. Appl. in Genetics and Molecular Biology, 3, 2004. (pdf)
• S. Gangaputra and D. Geman, "Self-normalized linear tests," Proceedings CVPR 2004, 2, 616-622, 2004 (pdf)
• X. Fan and D. Geman, "Hierarchical object indexing and sequential learning," Proceedings ICPR 2004, 3, 65-68, 2004. (pdf)

2003

• D. Geman, "Coarse-to-fine classification and scene labeling," Nonlinear Estimation and Classification (eds. D. D. Denison et al.), Lecture Notes in Statistics. New York: Springer-Verlag, 31-48, 2003. (pdf)
• C. d'Avignon and D. Geman, "Tree-structured neural decoding ," Journal of Machine Learning Research, 4, 743-754, 2003. (pdf)

2002

• H. Sahbi, D. Geman and N. Boujemaa, "Face detection using coarse-to-fine support vector classifiers," Proceedings ICIP-02, 3, 925-928, 2002. (pdf)
• F. Fleuret and D. Geman, "Fast face detection with precise pose estimation," Proceedings ICPR2002, 1, 235-238, 2002. (pdf)
• S. Krempp, D. Geman and Y. Amit, "Sequential learning with reusable parts for object detection," Technical Report, 2002. (pdf)

2001

• F. Fleuret and D. Geman, "Coarse-to-fine face detection," Inter. Journal of Computer Vision, 41, 85-107, 2001. (pdf)
• D. Geman and B. Jedynak, "Model-based classification trees," IEEE Trans. Info. Theory, 47, 1075-1082, 2001. (pdf)
• D. Geman and R. Moquet, "Q & A models for interactive search," Technical Report, 2001. (pdf)
• D. Geman, "Interrogation Bayesienne d'une base de donnees," Proceedings 33rd Journees de Statistique, Nantes, 15-20, 2001.

Before 2000

• D. Geman and R. Moquet, "A stochastic model for image retrieval," Proc. RFIA 200, Paris, February, 2000. (pdf)
• F. Fleuret and D. Geman, "Graded learning for object detection," Proceedings, IEEE Workshop on Statistical and Computational Theories of Vision, Fort Collins, CO, June, 1999.
• D. Geman and A. Koloydenko, "Invariant statistics and coding of natural microimages," Proceedings, IEEE Workshop on Statistical and Computational Theories of Vision, Fort Collins, CO, June, 1999. (pdf)
• Y. Amit and D. Geman, "A computational model for visual selection," Neural Computation, 11, 1691-1715, 1999. (pdf)
• C. Li and D. Geman, "Active testing at multiple resolutions," Proceedings ASA Conference, Baltimore, 1999.
• Y. Amit, D. Geman and B. Jedynak, "Efficient focusing and face detection," Face Recognition: From Theory to Applications, eds. H. Wechsler et al, NATO ASI Series F, Springer-Verlag, Berlin, 157-173, 1998. (pdf)
• F. Jung, B. Jednyak and D. Geman, "Recognizing buildings in aerial images," Automatic Extraction of Man-Made Objects from Aerial and Space Images, II, Birkhauseer (Basel), Ascona, 173-182, May, 1997.
• Y. Amit, D. Geman and K. Wilder, "Joint induction of shape features and tree classifiers," IEEE Trans. Pattern Anal. Mach. Intell., 19, 1300-1305, 1997. (pdf)
• Y. Amit and D. Geman, "Shape quantization and recognition with randomized trees," Neural Computation., 9, 1545-1588, 1997. (pdf)
• D. Geman and B. Jedynak, "An active testing model for tracking roads from satellite images," IEEE Trans. Pattern Anal. Mach. Intell, 18, 1-14, 1996. (pdf)
• D. Geman and C. Yang, "Nonlinear image recovery with half-quadratic regularization," IEEE Trans. Image Processing, 4, 932-946, 1995. (pdf)
• S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell, 6, 721-741, 1984. (pdf)