My vitae (out of date).
My courses: Stat220, Stat311, Stat427, Stat/Math394,
Stat/Math390.
My short course material.
My son's music and pictures.
My wife's work.
My other creations.
My patent.
Journal Articles:
- 47. Marzban, C., R. Viswanathan, U. Yurtsever 2013:
Life after Earth. To be submitted to Biology Direct.
http://arxiv.org/abs/1306.0071
- 46. Marzban, C., Scott Sandgathe, James D. Doyle, Nicholas C. Lederer 2013:
Variance-based Sensitivity Analysis: COAMPS.
Submitted to Monthly Weather Review.
- 45. Marzban, C., R. Illian, D. Morison, P. D. Mourad 2013: A double-gaussian, percentile-based method for estimating maximum blood
flow velocity. Accepted at the Journal of Ultrasound in Medicine.
- 44. Marzban, C. 2013: Variance-based Sensitivity Analysis: An illustration on the Lorenz '63 model. Accepted at Monthly Weather Review.
- 43. Marzban, C., R. Illian, D. Morison, P. D. Mourad 2013: Within-group and between-group correlation: Illustration on
noninvasive
estimation of intracranial pressure. Submitted to the IEEE Journal of Biomedical and Health Informatics. (A related paper with more detail
has not been submitted for publication).
- 42. Marzban, C., R. Illian, D. Morison, A. Moore, M. Kliot, M. Czosnyka, P. D. Mourad 2013: A method for estimating zero-flow pressure and intracranial pressure. Journal of Neurosurgical Anaesthesiology, 25(1), 25-32.
- 41. Marzban, C. 2012: Displaying economic value. Weather and Forecasting, 27 (6), 1604-1612.
- 40. Yurtsever, U., C. Marzban, M. Meila, 2011: On the gravitational inverse problem. Applied Mathematical Sciences, Vol. 5, no. 57, 2839-2854.
- 39. Marzban, C. and S. Sandgathe 2010:
Optical Flow for verification.
Weather and Forecasting, 25 (5), 1479-1494.
- 38. Marzban, C., R. Wang, F. Kong, S. Leyton 2011:
On the effect of correlations on Rank Histograms :
Reliability of Temperature and wind-speed forecasts from Fine-scale Ensemble Reforecasts.
Monthly Weather Review, 139(1), 295-310.
An intimately related paper is by Dan Wilks .
- 37. Mourad, P. D., C. Marzban, and M. Kliot 2009:
Towards predicting intracranial pressure using transcranial Doppler and
arterial blood pressure data.
J. Acoust. Soc. Am., 125, 2514.
- 36. Marzban, C., S. Sandgathe, H. Lyons, N. Lederer 2009:
Three Spatial Verification Techniques:
Cluster Analysis, Variogram, and Optical Flow. Wea. Forecasting,
24(6), 1457-1471.
- 35. Kim, A. Y., C. Marzban, D. Percival, W. Stuetzle 2009:
Using labeled Data to evaluate change detectors
in a multivariate streaming environment. Signal Processing, 89(12), 2529-2536;
doi:10.1016/j.sigpro.2009.04.011.
- 34. Marzban, C. and S. Sandgathe 2009: Verification with
variograms. Weather and Forecasting, Vol. 24, No. 4,
1102-1120.
- 33. Marzban, C., S. Sandgathe, and H. Lyons 2008: An
Object-oriented Verification of Three NWP Model
Formulations via Cluster Analysis: An objective and a subjective analysis.
Monthly Weather Review, Vol. 136, No. 9., 3392-3407.
- 32. Marzban, C., S. Sandgathe, 2008:
Cluster Analysis for Object-Oriented Verification of Fields: A Variation. Monthly Weather Review, Vol. 136, 1013-1025.
- 31. Marzban, C., S. Leyton, and B. Colman 2007:
Ceiling & Visibility forecasts via Neural Nets.
Wea. Forecasting, Vol. 22, No. 3, 466-479.
- 30. Marzban, C., S. Sandgathe 2006: Cluster analysis for
verification of precipitation fields. Wea. Forecasting, Vol. 21,
No. 5, 824-838.
- 29. Marzban, C., S. Sandgathe, E. Kalnay, 2005:
MOS, Perfect Prog, and Reanalysis Data. Monthly Weather Review, Vol.
134, No. 2, 657-663.
- 28. Trites, A. W. et al, 2004: Bottom-up forcing and the decline of
Steller sea lions in Alaska: Assessing the ocean
climate hypothesis. Fisheries Oceanography, doi:10.1111/j.1365-2419.2006.00408.
- 27. Hennon, C., C. Marzban, J. S. Hobgood, 2004: Improving tropical cyclogenesis statistical model forecasts
through the application of a neural network classifier. Wea. Forecasting.,
Vol. 20, No. 6, 1073-1083.
- 26. Marzban, C. 2004: The ROC Curve and the Area
Under it as a Performance Measure. Weather and Forecasting, Vol. 19,
No. 6, 1106-1114.
- 25. Marzban, C., 2003: A Neural Network for
Post-processing Model Output: ARPS . Monthly Weather Review, Vol. 131,
No. 6., pp. 1103-1111.
- 24. Drton, M., Marzban, C., P. Guttorp, & J. T. Scahefer, 2003:
A Markov Chain Model of Tornadic Activity. Monthly Weather Review,
Vol 131, No. 12, 2941-2953. An earlier version of the paper is by Marzban &
Guttorp .
- 23. Marzban, C., and A. Witt, 2001: A Bayesian
Neural Network for Hail Size Prediction. Wea. Forecasting, Vol. 16,
No. 5, pp. 600-610. A neural network for the detection of hail can be
found here .
- 22. Marzban, C., and J. Schaefer, 2001: The
Correlation Between U.S. Tornados and Pacific Sea Surface Temperature.
Monthly Weather Review, Vol. 129, No. 4, 884-895.
- 21. Marzban, C. 2000: A neural network for tornado
diagnosis. Neural Computing and Applications, Vol. 9 (2), 133-141.
- 20. Marzban, C., E. D. Mitchell, G. Stumpf, 1999: The
notion of ``best predictors:" An application to tornado prediction.
Weather and Forecasting, Vol. 14, No. 6, 1007-1016.
- 19. Marzban, C., V. Lakshmanan, 1999: On the uniqueness
of Gandin and Murphy's equitable performance measures. Monthly Weather
Review, Vol. 127, No.6, 1134-1136.
- 18. Marzban, C., G. J. Stumpf, 1998: A Neural Network for Tornado and/or
Damaging Wind Prediction Based on Doppler Radar-derived Attributes.
Microcomputer Applications, Vol. 17, 21-28.
- 17. Marzban, C., G. J. Stumpf, 1998: A neural network
for damaging wind prediction, Weather and Forecasting, Vol. 13, No.1,
151-163.
- 16. Marzban, C. 1998: Scalar measures of performance in
rare-event situations, Weather and Forecasting, Vol. 13, 753-763.
- 15. Marzban, C. 1998: Bayesian probability and scalar
performance measures in gaussian models, Journal of Applied Meteorology,
Vol. 37, 72-82.
- 14. Marzban, C., H. Paik, and G. Stumpf, 1997: Neural
networks vs. gaussian discriminant analysis, AI Applications, Vol. 10,
No.1, 49-58.
- 13. Marzban, C., G. J. Stumpf, 1996: A neural network
for tornado prediction ..., Journal of Applied Meteorology, Vol. 35, 617.
- 12. Kantowski, R., C. Marzban, 1995: A Neural Network for Locating the
Primary Vertex in a Pixel Detector. Nuclear Instruments and Methods in
Physics Research, A 355, 582.
- 11. Paik, H., C. Marzban, 1995: Predicting Television Extreme-viewer vs.
Non-viewer: A Neural Network Analysis. Human Communication Research, Vol. 22,
284.
- 10. Marzban, C., R. Viswanathan, 1994: Stochastic Neural
Networks with the Weighted Hebb Rule, Physics Letters A Vol. 191, 127.
- 9. Kantowski, R., C. Marzban, 1992: One-loop Vilkovisky-DeWitt
Counterterms for Two-dimensional Gravity Plus Scalar Field Theory. Phys.
Rev. D46.
- 8. Marzban, C., R. Viswanathan, 1992: Matrix Models With
\gamma_{string}>0. Phys. Lett. B277, 289.
- 7. Marzban, C., R. Viswanathan, 1991: Matrix Models With Non-even Potentials.
Int. Journ. of Mod. Phys. A6, 2559.
- 6. Marzban, C., 1990: Morse Theory Applied to N=1 and 2 Superconformal
Theories. Phys. Lett. B238, 257.
- 5. Marzban, C., 1990: Remarks on the Landau-Ginzburg Potential and
RG-flow for SU(2)-coset Models. Phys. lett. B236, 298.
- 4. Marzban, C., B. F. Whiting, H. Van Dam, 1989: Hamiltonian Reduction for
Massive Fields Coupled to Sources. Jour. Math. Phys. 30, 1877.
- 3. Kikuchi, Y., C. Marzban, 1987: Two-loop Modular Invariance and Proper
Spin-Statistics Projection for General Boundary Conditions. Phys. Rev. D36,
2583.
- 2. Kikuchi, Y., C. Marzban, 1987: Low-energy Effective Lagrangian of
Heterotic String Theory. Phys. Rev. D35, 1400.
- 1. Kikuchi, Y., C. Marzban, Y. J. Ng, 1986: Heterotic String Modifications
of Einstein's and Yang-Mills' Actions. Phys. Lett. B176, 57.
Technical Reports and Unpublished/In-Progress Work:
- 5. Marzban, C., U. Yurtsever, 2011: Baby Morse theory for statistical inference from point cloud data.
- 4. Stuetzle, W., D. Percival, and C. Marzban 2010:
Targeted event detection.
- 3. Marzban, C., S. Sandgathe, D. Morison, N. Lederer, 2010:
On the relation between model parameters and forecast parameters.
- 2. Marzban, C., D. Lettenmaier, and L. Bowling, 2004:
Trends in Extreme Precipitation and Streamflow.
- 1. Marzban, C. 1997: Local minima in Bootstrapping.
Selected Conference Papers:
- Marzban, C., and U. Yurtsever 2011: Baby Morse theory in data analysis.
Paper at the workshop on Knowledge Discovery, Modeling and Simulation (KDMS), held
in conjunction with the 17th ACM SIGKDD Conference on Knowledge Discovery and Data
Mining, San Diego, CA., August 21-24.
- Marzban, C. 2011: Sensitivity Analysis in linear and nonlinear models: A review. Paper presented at the 9th Conference
on Artificial Intelligence, at the 91st American Meteorological Society Annual
Meeting, Seattle, Jan. 23-27.
- Marzban, C. 2008: Quantile Regression. Invited
paper presented at the joint session between AI and Prob & Stats Conference. 88th
American Meteorological Society Annual Meeting, New Orleans, Jan. 20-24.
- Marzban, C., S. Sandgathe, and H. Lyons 2007: Assessment of an automatic, object-oriented approach to the verification of spatial fields . Paper presented at
7th Euopean Meteorological Society Annual MeetingEl Escorial, Spain, October.
- Marzban, C. 2004: Probabilistic Forecasts in Meteorology. Talk presented at a Neural Information Processing Systems, 2004,
workshop on Calibration and Probabilistic Prediction in Supervised Learning.
Whistler, Canada.
- Marzban, C. 1998: Bayesian inference in neural
networks. 78th meeting of the American Meteorological Society,
Probability and Statistics Session, Phoenix Arizona, January.
- Marzban, C., G. J. Stumpf, 1996: A Neural Network for Tornado and/or
Severe Weather Prediction Based on Doppler Radar-derived Attributes.
10th Annual Mid-American Symposium on Emerging Computer Technologies,
University of Oklahoma, October 28-29. (Top-paper Award.)
- Marzban, C., R. Viswanathan, 1993: Stochastic Neural Networks and the
Weighted Hebb Rule. Proceedings of the IJCNN conference, Nagoya, Japan.
Books:
Artificial Intelligence Methods in the Environmental Sciences, 2008;
Springer-Verlag. Co-editor and contributor to 2 chapters.
How to Contact me:
Dept. of Statistics
University of Washington
Box 354322
Seattle, WA 98195-4322
Tel: 206.685-7428
Fax: 206.685.7419
marzban at stat.washington.edu
Applied Physics Laboratory
University of Washington
Box 355640
Seattle, WA 98105-6698
Tel: 206.221.4361
Fax: 206.543.1301
marzban at apl.washington.edu
Caren Marzban, Ph.D.