Finding Golf Courses: The Ultra High Tech Approach. - Neal R. Harvey; Simon Perkins; Steven P. Brumby; James Theiler; Reid B. Porter; A. Cody Young; Anil K. Varghese; John J. Szymanski; Jeffrey J. Bloch (EvoWorkshops, 2000)

Algorithmic transformations in the implementation of K- means clustering on reconfigurable hardware. - Mike Estlick; Miriam Leeser; James Theiler; John J. Szymanski (FPGA, 2001)

Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery. - Christopher C. Funk; James Theiler; Dar A. Roberts; Christoph C. Borel (IEEE Trans. Geosci. Remote. Sens., 2001)

Modified Kernel-based Nonlinear Feature Extraction. - Junshui Ma; Simon Perkins; James Theiler; Stanley C. Ahalt (ICMLA, 2002)

Comparison of GENIE and conventional supervised classifiers for multispectral image feature extraction. - Neal R. Harvey; James Theiler; Steven P. Brumby; Simon Perkins; John J. Szymanski; Jeffrey J. Bloch; Reid B. Porter; Mark Galassi; A. Cody Young (IEEE Trans. Geosci. Remote. Sens., 2002)

Online Feature Selection using Grafting. - Simon Perkins; James Theiler (ICML, 2003)

Weighted Order Statistic Classifiers with Large Rank-Order Margin. - Reid B. Porter; Damian Eads; Don R. Hush; James Theiler (ICML, 2003)

Firing correlations improve detection of moving bars. - Garrett T. Kenyon; James Theiler; David W. Marshak; Bartlett Moore; Janelle Jeffs; Bryan J. Travis (IJCNN, 2003)

Optimizing Digital Hardware Perceptrons for Multi-Spectral Image Classification. - Reid B. Porter; Neal R. Harvey; Simon Perkins; James Theiler; Steven P. Brumby; Jeffrey J. Bloch; Maya B. Gokhale; John J. Szymanski (J. Math. Imaging Vis., 2003)

Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space. - Simon Perkins; Kevin Lacker; James Theiler (J. Mach. Learn. Res., 2003)

Accurate On-line Support Vector Regression. - Junshui Ma; James Theiler; Simon Perkins (Neural Comput., 2003)

Experience with a Hybrid Processor: K-Means Clustering. - Maya B. Gokhale; Janette Frigo; Kevin McCabe; James Theiler; Christophe Wolinski; Dominique Lavenier (J. Supercomput., 2003)

Approach to Target Detection based on Relevant Metric for Scoring Performance. - James Theiler; Neal R. Harvey; Nancy A. David; John M. Irvine (AIPR, 2004)

Correlated Firing Improves Stimulus Discrimination in a Retinal Model. - Garrett T. Kenyon; James Theiler; John S. George; Bryan J. Travis; David W. Marshak (Neural Comput., 2004)

A theory of the Benham Top based on center-surround interactions in the parvocellular pathway. - Garrett T. Kenyon; Dan Hill; James Theiler; John S. George; David W. Marshak (Neural Networks, 2004)

Two realizations of a general feature extraction framework. - Junshui Ma; James Theiler; Simon Perkins (Pattern Recognit., 2004)

Stimulus-specific oscillations in a retinal model. - Garrett T. Kenyon; Bryan J. Travis; James Theiler; John S. George; Greg J. Stephens; David W. Marshak (IEEE Trans. Neural Networks, 2004)

Detecting a malicious executable without prior knowledge of its patterns. - Dongming Cai; James Theiler; Maya B. Gokhale (Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security, 2005)

Online feature selection for pixel classification. - Karen A. Glocer; Damian Eads; James Theiler (ICML, 2005)

Resolution Enhancement of Multilook Imagery for the Multispectral Thermal Imager. - Amy E. Galbraith; James Theiler; Kurtis J. Thome; Richard W. Ziolkowski (IEEE Trans. Geosci. Remote. Sens., 2005)

Incorporating Spatial Contiguity into the Design of a Support Vector Machine Classifier. - Murat Dundar; James Theiler; Simon Perkins (IGARSS, 2006)

Effect of signal contamination in matched-filter detection of the signal on a cluttered background. - James Theiler; Bernard R. Foy (IEEE Geosci. Remote. Sens. Lett., 2006)

Parallel random number generators for sequences uniformly distributed over any range of integers. - Richard Kuehnel; James Theiler; Yuke Wang (IEEE Trans. Circuits Syst. I Regul. Pap., 2006)

Comparison of feature selection and classification algorithms in identifying malicious executables. - D. Michael Cai; Maya B. Gokhale; James Theiler (Comput. Stat. Data Anal., 2007)

Detection of ephemeral changes in sequences of images. - James Theiler; Steven M. Adler-Golden (AIPR, 2008)

EC-GLRT: Detecting Weak Plumes in Non-Gaussian Hyperspectral Clutter Using an Elliptically-Contoured Generalized Likelihood Ratio Test. - James Theiler; Bernard R. Foy (IGARSS (1), 2008)

Web-based design and evaluation of T-cell vaccine candidates. - James Thurmond; Hyejin Yoon; Carla Kuiken; Karina Yusim; Simon Perkins; James Theiler; Tanmoy Bhattacharya 001; Bette T. Korber; Will Fischer 001 (Bioinform., 2008)

GNU Scientific Library - Reference Manual, Third Edition, for GSL Version 1.12. - Mark Galassi; Jim Davies; James Theiler; Brian Gough; Gerard Jungman (Network Theory Ltd, 2009)

Uncorrelated versus independent elliptically-contoured distributions for anomalous change detection in hyperspectral imagery. - James Theiler; Clint Scovel (Computational Imaging, 2009)

A change detection approach to moving object detection in low fame-rate video. - Reid B. Porter; Neal R. Harvey; James Theiler (Visual Information Processing, 2009)

A structural framework for anomalous change detection and characterization. - Lakshman Prasad; James Theiler (Visual Information Processing, 2009)

Weak signal detection in hyperspectral imagery using sparse matrix transform (smt) covariance estimation. - Guangzhi Cao; Charles A. Bouman; James Theiler (WHISPERS, 2009)

Improved change detection with local co-registration adjustments. - Brendt Wohlberg; James Theiler (WHISPERS, 2009)

Symmetrized local co-registration optimization for anomalous change detection. - Brendt Wohlberg; James Theiler (Computational Imaging, 2010)

Block-diagonal representations for covariance-based Anomalous change detectors. - Anna Matsekh; James Theiler (IGARSS, 2010)

Using support vector machines for anomalous change detection. - Ingo Steinwart; James Theiler; Daniel Llamocca (IGARSS, 2010)

Sparse matrix transform for fast projection to reduced dimension. - James Theiler; Guangzhi Cao; Charles A. Bouman (IGARSS, 2010)

Statistics for characterizing data on the periphery. - James Theiler; Don R. Hush (IGARSS, 2010)

Ship detection in satellite imagery using rank-order grayscale hit-or-miss transforms. - Neal R. Harvey; Reid B. Porter; James Theiler (Visual Information Processing, 2010)

Radial kernels and their reproducing kernel Hilbert spaces. - Clint Scovel; Don R. Hush; Ingo Steinwart; James Theiler (J. Complex., 2010)

Elliptically Contoured Distributions for Anomalous Change Detection in Hyperspectral Imagery. - James Theiler; Clint Scovel; Brendt Wohlberg; Bernard R. Foy (IEEE Geosci. Remote. Sens. Lett., 2010)

Evaluating and improving local hyperspectral anomaly detectors. - Leonardo R. Bachega; James Theiler; Charles A. Bouman (AIPR, 2011)

Ellipsoid-simplex hybrid for hyperspectral anomaly detection. - James Theiler (WHISPERS, 2011)

Sparse Matrix Transform for Hyperspectral Image Processing. - James Theiler; Guangzhi Cao; Leonardo R. Bachega; Charles A. Bouman (IEEE J. Sel. Top. Signal Process., 2011)

Local principal component pursuit for nonlinear datasets. - Brendt Wohlberg; Rick Chartrand; James Theiler (ICASSP, 2012)

Detection of spectrally sparse anomalies in hyperspectral imagery. - James Theiler; Brendt Wohlberg (SSIAI, 2012)

Local Coregistration Adjustment for Anomalous Change Detection. - James Theiler; Brendt Wohlberg (IEEE Trans. Geosci. Remote. Sens., 2012)

Spatio-spectral anomalous change detection in hyperspectral imagery. - James Theiler (GlobalSIP, 2013)

Regression framework for background estimation in remote sensing imagery. - James Theiler; Brendt Wohlberg (WHISPERS, 2013)

Interactive Machine Learning in Data Exploitation. - Reid B. Porter; James Theiler; Don R. Hush (Comput. Sci. Eng., 2013)

Algorithms for Multispectral and Hyperspectral Image Analysis. - Heesung Kwon; Xiaofei Hu; James Theiler; Alina Zare; Prudhvi Gurram (J. Electr. Comput. Eng., 2013)

Matched-Pair Machine Learning. - James Theiler (Technometrics, 2013)

An Overview of Background Modeling for Detection of Targets and Anomalies in Hyperspectral Remotely Sensed Imagery. - Stefania Matteoli; Marco Diani; James Theiler (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Hyperspectral target detection using manifold learning and multiple target spectra. - Amanda K. Ziemann; James Theiler; David W. Messinger (AIPR, 2015)

Right spectrum in the wrong place: a framework for local hyperspectral anomaly detection. - James Theiler; Amanda K. Ziemann (Computational Imaging, 2016)

Generic target response as a measure of regression accuracy in multispectral background estimation. - James Theiler (SSIAI, 2016)

Cracks in KRX: When more distant points are less anomalous. - James Theiler; Guen Grosklos (WHISPERS, 2016)

Problematic Projection to the In-Sample Subspace for a Kernelized Anomaly Detector. - James Theiler; Guen Grosklos (IEEE Geosci. Remote. Sens. Lett., 2016)

Segmented regression for spatio-spectral background estimation. - James Theiler; Amanda Ziemann (IGARSS, 2017)

Variable target detection using Simplex ACE. - Amanda Ziemann; James Theiler (IGARSS, 2017)

Selecting the selector: Comparison of update rules for discrete global optimization. - James Theiler; Beate G. Zimmer (Stat. Anal. Data Min., 2017)

Closed-Form Detector for Solid Sub-Pixel Targets in Multivariate T-Distributed Background Clutter. - James Theiler; Beate G. Zimmer; Amanda Ziemann (IGARSS, 2018)

Corrections to "Problematic Projection to the In-Sample Subspace for a Kernelized Anomaly Detector". - James Theiler; Guen Grosklos (IEEE Geosci. Remote. Sens. Lett., 2018)

Some Closed-Form Expressions for Absorptive Plume Detection. - James Theiler; Alan P. Schaum (IGARSS, 2020)

Data-driven Methods for Solving Large-scale Inverse Problems with Applications to Subsurface Imaging. - Youzuo Lin; James Theiler; Brendt Wohlberg; Yue Wu 009; Zhongping Zhang (SSIAI, 2020)

Identifying forest thinning using anomalous change detection on synthetic aperture radar data. - Elena C. Reinisch; James Theiler; Amanda Ziemann (SSIAI, 2020)

On the Detectability of Conflict: a Remote Sensing Study of the Rohingya Conflict. - Christopher X. Ren; Matthew T. Calef; Alice M. S. Durieux; Amanda Ziemann; James Theiler (SSIAI, 2020)

Cycle-Consistent Adversarial Networks for Realistic Pervasive Change Generation in Remote Sensing Imagery. - Christopher X. Ren; Amanda Ziemann; James Theiler; Alice M. S. Durieux (SSIAI, 2020)

Deep Snow: Synthesizing Remote Sensing Imagery with Generative Adversarial Nets. - Christopher X. Ren; Amanda Ziemann; James Theiler; Alice M. S. Durieux (CoRR, 2020)

Bayesian Detection of Solid Subpixel Targets. - James Theiler; Stefania Matteoli; Amanda Ziemann (IGARSS, 2021)

Absorptive Weak Plume Detection on Gaussian and Non-Gaussian Background Clutter. - James Theiler (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Physics-Consistent Data-Driven Waveform Inversion With Adaptive Data Augmentation. - Renán Rojas-Gómez; Jihyun Yang; Youzuo Lin; James Theiler; Brendt Wohlberg (IEEE Geosci. Remote. Sens. Lett., 2022)

Closed-Form Non-Parametric Admissible Detector for Solid Sub-Pixel Targets. - Stefania Matteoli; James Theiler (IGARSS, 2023)

Bayesian vs Generalized Likelihood Ratio Detection of Solid Sub-Pixel Targets. - James Theiler (IGARSS, 2023)

Physics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion. - Youzuo Lin; James Theiler; Brendt Wohlberg (IEEE Signal Process. Mag., 2023)

Bayesian Target Detection Algorithms for Solid Subpixel Targets in Hyperspectral Images. - Stefania Matteoli; James Theiler (IEEE Trans. Geosci. Remote. Sens., 2023)

Physics and Deep Learning in Computational Wave Imaging. - Youzuo Lin; Shihang Feng; James Theiler; Yinpeng Chen; Umberto Villa; Jing Rao; John James Greenhall; Cristian Pantea; Mark A. Anastasio; Brendt Wohlberg (CoRR, 2024)