Jones, HP, Chapman, GA, Harvey, KL, Pap, JM, Preminger, DG and others including Turmon, MJ (2009). “A comparison of feature classification methods for modeling solar irradiance variation,” Solar Image Analysis and Visualization, pp. 113–127, Springer. Document (link to DOI).

Bajracharya, Max, Howard, Andrew, Matthies, Larry, Tang, Benyang, and Turmon, Michael (2009). “Autonomous off-road navigation with end-to-end learning for the LAGR program,” Journal of Field Robotics, 26(1), pp. 3–25, Wiley. Document (CL#08-3542).

Norton, Charles D, Eldering, Annmarie, Turmon, Michael, and Parker, Jay (2009). “Extending OSSE beyond numerical weather prediction to new areas in Earth observing science,” IEEE Aerospace conference, pp. 1–10. Document (link to DOI) (CL#08-4487).

H. P. Jones, G. A. Chapman, K. L. Harvey, J. M. Pap, D. G. Preminger and others including M. J. Turmon (2008). “A Comparison of Feature Classification Methods for Modeling Solar Irradiance Variation,” Solar Physics, 248(2), pp. 323-337. Document (link to DOI).

M. Sarrel and M. Turmon (2008). “Improved Estimates of Spitzer Space Telescope Data Volumes with Error Bars,” AIAA SPACE 2008, p. 7696. Document (CL 08-0637).

A. Mahabal, S. G. Djorgovski, M. Turmon, J. Jewell, R. Williams and others (2008). “Automated probabilistic classification of transients and variables,” Astronomische Nachrichten: Astronomical Notes, 329(3), pp. 288-291. Document.

Bajracharya, Max, Tang, Benyang, Howard, Andrew, Turmon, Michael, and Matthies, Larry (2008). “Learning long-range terrain classification for autonomous navigation,” 2008 IEEE International Conference on Robotics and Automation, pp. 4018–4024. Document (CL#08-0301 (NTR 45146)).

Mahabal, A, Djorgovski, SG, Williams, R, Drake, A, Donalek, C and others including Turmon, M (2008). “Towards Real-Time Classification of Astronomical Transients,” AIP Conference Proceedings, vol. 1082, pp. 287–293. Document.

T. M. Chin, M. Turmon, J. Jewell, and M. Ghil (2007). “An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems,” Monthly Weather Review, 135(1), pp. 186-202.

A. Howard, M. Turmon, L. Matthies, B. Tang, A. Angelova, and E. Mjolsness (2006). “Towards learned traversability for robot navigation: From underfoot to the far field,” Journal of Field Robotics, 23(11/12), pp. 1005-1017. Document (link to DOI) (CL#06-3711).

Turmon, M, Chin, TM, Jewell, JB, and Ghil, M (2005). “Ensemble Smoothing and Markov Chain Monte Carlo for Data Assimilation in Highly Nonlinear Systems,” AGU Fall Meeting Abstracts, pp. IN41A–0309. Document.

Gy\Hori, L, Baranyi, T, Turmon, M, and Pap, JM (2004). “Study of differences between sunspot area data determined from ground-based and space-borne observations,” Advances in Space Research, 34(2), pp. 269–273, Elsevier. Document.

J. Pap, I. Ermolli, F. Gyorgi, and M. Turmon (2004). “Study of Solar Magnetic Feature Properties and Irradiance Variations,” 35th COSPAR Scientific Assembly, vol. 35. Document.

T. M. Chin, J. B. Jewell, and M. Turmon (2004). “Phase Changes and State Estimation for Non-linear Systems,” AGU Fall Meeting Abstracts, pp. NG31B-0877. Document.

M. Turmon (2004). “Symmetric Normal Mixtures,” Compstat 2004-Proceedings in Computational Statistics, pp. 1909-16, Physica-Verlag. Document (CL 04-1276).

L. Gyori, T. Baranyi, M. Turmon, and J.M. Pap (2004). “Study of differences between sunspot area data determined from ground-based and space-borne observations,” Adv. Space Res., 34, pp. 269-273.

M. Turmon, R. Granat, D. Katz, and J. Z. Lou (2003). “Tests and tolerances for High-Performance Software-Implemented Fault Detection,” IEEE Trans. Computers, 52(5), pp. 579–591. Document (CL 02-0735).

Turmon, Michael (2002). “Symmetry constraints within the EM algorithm for Gaussian mixtures,” Document.

J. Pap, H. Jones, M. Turmon, and L. Floyd (2002). “Study of the SOHO/VIRGO Irradiance Variations Using MDI and Kitt Peak Images,” Proc. SOHO-11 Workshop. ESA SP-508.

J. M. Pap, M. Turmon, L. Floyd, C. Frölich, and Ch. Wehrli (2002). “Total solar and spectral irradiance variations in solar cycles 21 to 23,” Adv. Space Res., 29(12), pp. 1923-1932, Elsevier. Document.

M. Turmon, J. Pap, and S. Mukhtar (2002). “Statistical Pattern Recognition for Labeling Solar Active Regions: Application to SoHO/MDI Imagery,” Astrophysical Journal, 568(1), pp. 396-407. Document (CL 01-2847).

E. Mjolsness, W. Fink, and M. Turmon (2001). “Stochastic Parameterized Grammars for Bayesian Model Composition,” Interface-2001, Costa Mesa, CA.

M. Turmon (2001). “Mixture models for labeling scientific imagery,” Mixtures 2001: Recent Developments in Mixture Modeling, Hamburg. Presentation (refereed).

E. Mjolsness and M. Turmon (2000). “Stochastic Parameterized Grammars for Bayesian Model Composition,” Neural Inform. Process. Syst. (NeurIPS). Invited talk, modeling workshop.

M. Turmon, R. Granat, and D. S. Katz (2000). “Software-Implemented Fault Detection for High-Performance Space Applications,” Proc. Intl. Conf. Dependable Systems and Networks, pp. 107–116. Document (CL 99-2014).

M. Turmon and R. Granat (2000). “Algorithm-Based Fault Tolerance for Spaceborne Computing: Basis and Implementations,” Proc. IEEE Aerospace Conference, pp. 411-420. Document (CL 00-0901).

M. Turmon, E. Mjolsness, V. Gluzman, and L. Ramsey (1999). “A Language for Probabilistic Modeling of Scientific Data,” Proc. Second Conf. Highly Structured Stochastic Systems, pp. 298–300, Pavia, Italy.

M. Turmon and S. Mukhtar (1998). “Representing Solar Active Regions with Triangulations,” COMPSTAT: Proc. Computational Statistics 13th Symposium, pp. 473-478, Bristol, UK. Document (CL 98-0761).

M. Turmon (1998). “Machine Learning and Statistics: The Interface,” Jour. American Statistical Association, 93(442), pp. 833-835.

M. Turmon, J. M. Pap, and S. Mukhtar (1998). “Automatically finding solar active regions using SoHO/MDI photograms and magnetograms,” Proc. SoHO 6/GONG '98 Workshop on Structure and Dynamics of the Sun, vol. 418, pp. 979-984. Document.

M. Turmon (1997). “Identification of Solar Features via Markov Random Fields,” Proc. Second Conf. International Assoc. for Statistical Computing (IASC-2), pp. 194–200. Document.

M. Turmon and J. Pap (1997). “Segmenting Chromospheric Images with Markov Random Fields,” Statistical Challenges in Modern Astronomy II, ed. G. Babu and E. Feigelson, pp. 408–411, Springer. Document.

M. Turmon, S. Mukhtar, and J. Pap (1997). “Bayesian Inference for Identifying Solar Active Regions,” Proc. Third Conf. on Knowledge Discovery and Data Mining, ed. D. Heckerman, H. Mannila, D. Pregibon, and R. Uthurusamy, pp. 267-270, MIT Press. Document (CL 97-0755).

M. Turmon and S. Mukhtar (1997). “Recognizing Chromospheric Objects via Markov Chain Monte Carlo,” Proc. IEEE Intl. Conf. Image Processing, vol. 3, pp. 320–323. Document (CL 97-1147).

M. Turmon (1995). Assessing Generalization of Feedforward Neural Networks, PhD thesis, Cornell. Document.

M. Turmon and T. L. Fine (1995). “Empirically Estimating Generalization Ability of Feedforward Neural Networks,” World Conference on Neural Networks, pp. 600-605. Invited paper. Document.

M. Turmon and T. L. Fine (1995). “Assessing Generalization of Feedforward Neural Networks,” IEEE International Symposium on Information Theory (ISIT), p. 168. Document (link to DOI).

M. Turmon and T. L. Fine (1994). “Sample Size Requirements for Feedforward Neural Networks,” Neural Information Processing Systems (NeurIPS), vol. 7, ed. G. , pp. 327-334, Morgan-Kauffman. Document.

M. J. Turmon and M. I. Miller (1994). “Maximum-Likelihood estimation of constrained means and Toeplitz covariances with application to direction-finding,” IEEE Trans. on Signal Processing, 42(5), pp. 1074–1086. Document.

T. L. Fine and M. Turmon (1993). “Sample Size Requirements of Feedforward Neural Network Pattern Classifiers,” IEEE International Symposium on Information Theory (ISIT), p. 432. Document (link to DOI).

M. J. Turmon (1990). “Maximum-likelihood estimation of constrained means and Toeplitz covariances with application to direction-finding,” M.S. thesis, Washington University, St. Louis.

M. I. Miller, M. J. Turmon, J. A. O'Sullivan, and D. L. Snyder (1988). “Spectrum Estimation via Maximum Likelihood Estimation of Toeplitz Constrained Covariances,” Proc. Fourth ASSP Workshop on Spectrum Estimation and Modeling, pp. 182-185. Document (link to DOI).