{"id":16,"date":"2017-05-15T06:06:37","date_gmt":"2017-05-15T06:06:37","guid":{"rendered":"http:\/\/www.keithdillon.com\/?page_id=16"},"modified":"2025-12-01T22:24:33","modified_gmt":"2025-12-01T22:24:33","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.keithdillon.com\/index.php\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<p>Listing publication, reports, and preprints here to share pdf versions.<\/p>\n<p>Google Scholar: <a href=\"https:\/\/scholar.google.com\/citations?user=jQ4cGy0AAAAJ&amp;hl=en\">https:\/\/scholar.google.com\/citations?user=jQ4cGy0AAAAJ&amp;hl=en<\/a><\/p>\n<p><strong>Publications &amp; Reports <\/strong><\/p>\n<div class=\"csl-bib-body\">\n<div class=\"csl-entry\">\n<ul>\n<li>Keith Dillon, &#8220;Sources and Sinks in Functional Brain Networks&#8221;, Report 2025 (<a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Sources and Sinks in Functional Brain Networks.pdf\">pdf<\/a>)<\/li>\n<li>Keith Dillon, &#8220;Artificial Intelligence for Global Optimization of Blind 3D Reconstruction from Time-of-Flight Cameras&#8221;, 86th JSAP Autumn meeting, 2025 (<a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Artificial Intelligence for Global Optimization of Blind 3D Reconstruction from Time-of-Flight Cameras.pdf\">pdf<\/a>)<\/li>\n<li>Keith Dillon, &#8220;<a href=\"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/12675\/126750Z\/Model-based-machine-learning-for-computational-reconstruction-of-opacity-and\/10.1117\/12.2676917.short\">Model-based machine learning for computational reconstruction of opacity and missing information<\/a>&#8220;, Proc. SPIE 12675, Applications of Machine Learning 2023, 126750Z, 2023<\/li>\n<li>Keith Dillon and Jeffrey Chomyn, &#8220;<a href=\"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/12666\/1266604\/Optimization-of-freeform-spectacle-lenses-based-on-high-order-aberrations\/10.1117\/12.2676950.short#_=_\">Optimization-of-freeform-spectacle-lenses-based-on-high-order-aberrations<\/a>&#8220;, Proc. SPIE 12666, Current Developments in Lens Design and Optical Engineering XXIV, 1266604, 2023 (<a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Optimization of freeform spectacle lenses based on high-order aberrations.pdf\">pdf<\/a>)<\/li>\n<li>K. Dillon, &#8220;Calculus for Deep Learning, with Vectors, Matrices, and a few Tuples&#8221;, Report 2022 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Calculus for Deep Learning, with Vectors, Matrices, and a few Tuples.pdf\">(pdf)<\/a><\/li>\n<li>Keith Dillon, &#8220;<a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-030-73973-7_17\">Efficient Partitioning of Partial Correlation Networks<\/a>&#8220;. In: Torsello A., Rossi L., Pelillo M., Biggio B., Robles-Kelly A. (eds) Structural, Syntactic, and Statistical Pattern Recognition. S+SSPR 2021. Lecture Notes in Computer Science, vol 12644. Springer, Cham. 2021 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Efficient Partitioning of Partial Correlation Networks.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon, &#8220;A first-order optimization method for learning to reconstruct opacity in computational imaging&#8221;, Report 2021 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/A first-order optimization method for learning to reconstruct opacity in computational imaging.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon and Y.-P. Wang, &#8220;<a class=\"gsc_a_at\" href=\"https:\/\/doi.org\/10.1016\/j.jneumeth.2020.108628\" data-href=\"\/citations?view_op=view_citation&amp;hl=en&amp;user=jQ4cGy0AAAAJ&amp;sortby=pubdate&amp;citation_for_view=jQ4cGy0AAAAJ:u_35RYKgDlwC\">Resolution-based spectral clustering for brain parcellation using functional MRI<\/a>,&#8221;<em>Journal of Neuroscience Methods<\/em> 335, 108628, 2020<\/li>\n<li>A. Ambrose, K. Dillon, &#8220;<a class=\"gsc_a_at\" data-href=\"\/citations?view_op=view_citation&amp;hl=en&amp;user=jQ4cGy0AAAAJ&amp;sortby=pubdate&amp;citation_for_view=jQ4cGy0AAAAJ:dfsIfKJdRG4C\">Robust neural network for wavefront reconstruction using Zernike coefficients<\/a>&#8220;, Applications of Machine Learning 11511, 115110N, 2020<\/li>\n<li>K. Dillon, &#8220;Feature Level Malware Obfuscation in Deep Learning&#8221;, <a href=\"https:\/\/arxiv.org\/pdf\/2002.05517\">https:\/\/arxiv.org\/pdf\/2002.05517<\/a>, 2020<\/li>\n<li>K. Dillon, &#8220;Quadratic Programming with Keras&#8221;, Report 2019 (<a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Quadratic Programming with Keras.pdf\">pdf<\/a>)<\/li>\n<li>Keith Dillon, Yu-Ping Wang, &#8221; <a href=\"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/10394\/103940E\/A-regularized-clustering-approach-to-brain-parcellation-from-functional-MRI\/10.1117\/12.2274846.short?SSO=1\">A regularized clustering approach to brain parcellation from functional MRI data<\/a>&#8220;, Proc. SPIE 10394, Wavelets and Sparsity XVII, 103940E, 2017 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/A regularized clustering approach to brain parcellation from functional MRI data.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon, V. Calhoun, and Y.-P. Wang, \u201c<a href=\"http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0165027016302709\">A robust sparse-modeling framework for estimating schizophrenia biomarkers from fMRI<\/a>,\u201d<em>Journal of Neuroscience Methods<\/em>, vol. 276, pp. 46\u201355, Jan. 2017 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/A robust sparse-modeling framework for estimating schizophrenia biomarkers from fMRI.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon, \u201c<a href=\"http:\/\/biomedicaloptics.spiedigitallibrary.org\/article.aspx?articleid=2592809\">Fast and robust estimation of ophthalmic wavefront aberrations<\/a>,\u201d <em>J. Biomed. Opt<\/em>, vol. 21, no. 12, pp. 121511\u2013121511, 2016. <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Fast%20and%20Robust%20Estimation%20of%20Ophthalmic%20Wavefront%20Aberrations.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon, Y. Fainman, and Y.-P. Wang, \u201c<a href=\"http:\/\/electronicimaging.spiedigitallibrary.org\/article.aspx?articleid=2557156\">Computational estimation of resolution in reconstruction techniques utilizing sparsity, total variation, and nonnegativity<\/a>,\u201d <em>J. Electron. Imaging<\/em>, vol. 25, no. 5, pp. 053016\u2013053016, 2016 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Computational Estimation of Resolution in Reconstruction Techniques Utilizing Sparsity, Total Variation, and Non-negativity.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon and Y.-P. Wang, \u201c<a href=\"http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0165168415004363\">Imposing uniqueness to achieve sparsity<\/a>,\u201d <em>Signal Processing<\/em>, vol. 123, pp. 1\u20138, Jun. 2016 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Imposing Uniqueness to Achieve Sparsity.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon and Y. Fainman, \u201c<a href=\"http:\/\/link.springer.com\/article\/10.1007\/s11760-016-0889-2\">Element-wise uniqueness, prior knowledge, and data-dependent resolution<\/a>,\u201d <i>SIViP<\/i>, pp. 1\u20138, Apr. 2016 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Element-wise uniqueness, prior knowledge, and data-dependent resolution.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon and Y.-P. Wang, \u201c<a href=\"http:\/\/ieeexplore.ieee.org\/document\/7591350\/\">On efficient meta-filtering of big data<\/a>,\u201d in <i>Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the<\/i>, pp. 2958\u20132961, 2016 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/On Efficient Meta-Filtering of Big Data.pdf\">(pdf) <\/a><\/li>\n<li class=\"csl-right-inline\">K. Dillon and Y.-P. Wang, \u201c<a href=\"http:\/\/ieeexplore.ieee.org\/document\/7590905\/\">An image resolution perspective on functional activity mapping<\/a>,\u201d in <i>Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference<\/i>, pp. 1139\u20131142, 2016 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/An Image Resolution Perspective on Functional Activity Mapping.pdf\">(pdf) <\/a><\/li>\n<li class=\"csl-right-inline\"><a href=\"http:\/\/escholarship.org\/uc\/item\/5332d3jh\">Optimization in Computational Imaging and Inverse Problems<\/a> University of California San Diego 2014<\/li>\n<li>K. Dillon and Y. Fainman, \u201c<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pubmed\/23545983\">Bounding pixels in computational imaging<\/a>,\u201d <em>Appl. Opt.<\/em>, vol. 52, no. 10, pp. D55\u2013D63, Apr. 2013 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Bounding pixels in computational imaging.pdf\">(pdf)<\/a><\/li>\n<li>K. J. Dillon and Y. Fainman, \u201c<a href=\"https:\/\/www.osapublishing.org\/abstract.cfm?uri=COSI-2012-CTu4B.3\">Computational Lightcurve Imaging<\/a>,\u201d in <i>Computational Optical Sensing and Imaging<\/i>, p. CTu4B.3. 2012<\/li>\n<li class=\"csl-right-inline\">\n<div class=\"csl-right-inline\">K. J. Dillon and Y. Fainman, \u201cNonlinear Tomographic Imaging of Scattering and Attenuation,\u201d in <i>Frontiers in Optics<\/i>, p. FTuL2. 2011<\/div>\n<\/li>\n<li>K. Dillon and Y. Fainman, \u201c<a href=\"https:\/\/www.osapublishing.org\/josaa\/abstract.cfm?uri=josaa-27-6-1347\">Depth sectioning of attenuation<\/a>,\u201d <em>J. Opt. Soc. Am. A<\/em>, vol. 27, no. 6, pp. 1347\u20131354, Jun. 2010 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/depth sectioning of attenuation josaa-27-6-1347.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon and Y. Fainman, \u201c<a href=\"https:\/\/www.osapublishing.org\/ao\/abstract.cfm?uri=ao-49-13-2529\">Computational confocal tomography for simultaneous reconstruction of objects, occlusions, and aberrations<\/a>,\u201d <em>Appl. Opt.<\/em>, vol. 49, no. 13, pp. 2529\u20132538, May 2010 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Computational confocal tomography for simultaneous reconstruction of objects, occlusions, and aberrations.pdf\">(pdf)<\/a><\/li>\n<li>Keith J. Dillon and Yeshaiahu Fainman, \u201cRejecting out-of-Focus Attenuation,\u201d in Imaging Systems, p. IWA3. 2010<\/li>\n<li>K. Dillon, &#8220;Focus optimization in a Computational Confocal Microscope&#8221;, Report 2010 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Focus optimization in a Computational Confocal Microscope.pdf\">(pdf)<\/a><\/li>\n<li>K. Dillon, \u201c<a href=\"https:\/\/www.osapublishing.org\/vjbo\/abstract.cfm?uri=josaa-26-8-1839\">Bilinear wavefront transformation<\/a>,\u201d <em>J. Opt. Soc. Am. A<\/em>, vol. 26, no. 8, pp. 1839\u20131846, 2009 <a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Bilinear%20wavefront%20transformation.pdf\">(pdf) <\/a><\/li>\n<li>K. J. Dillon and Y. Fainman, \u201cComputational Confocal Scanning Tomography,\u201d in <i>Frontiers in Optics 2009\/Laser Science XXV\/Fall 2009 OSA Optics &amp; Photonics Technical Digest<\/i>, p. JTuC7.Y. 2009<\/li>\n<li class=\"csl-right-inline\">Liu, L. Warden, K. J. Dillon, G. Mills, and A. W. Dreher, \u201cA novel high-resolution and large-range diffractive wavefront sensor,\u201d <i>Proceedings of SPIE<\/i>, vol. 6306, no. 1, p. 63060J\u201363060J\u20136, Aug. 2006<\/li>\n<li class=\"csl-right-inline\">Y. Liu, L. Warden, K. Dillon, G. Mills, and A. Dreher, \u201cZ-View diffractive wavefront sensor: principle and applications,\u201d <i>Proceedings of SPIE<\/i>, vol. 6018, no. 1, pp. 601809-601809\u20139, Dec. 2005<\/li>\n<li class=\"csl-right-inline\">K. J. Dillon, B. S. Denney, and R. J. P. de Figueiredo, \u201c<a href=\"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/5095\/0000\/Estimating-3D-orientation-from-1D-projections-with-applications-to-radar\/10.1117\/12.487500.full\">Estimating 3D orientation from 1D projections with applications to radar<\/a>,\u201d <i>Proceedings of SPIE<\/i>, vol. 5095, no. 1, pp. 216\u2013223, Sep. 2003 (<a href=\"https:\/\/www.keithdillon.com\/papers_preprints\/Estimating 3-D Orientation from 1-D Projections.pdf\">pdf<\/a>)<\/li>\n<li class=\"csl-right-inline\">B. S. Denney, K. Estabridis, R. J. P. de Figueiredo, and K. J. Dillon, \u201cSome results from scattering-based tomography for HRR and SAR prediction,\u201d presented at the Algorithms for Synthetic Aperture Radar Imagery X, vol. 5095, pp. 194\u2013205. 2003<\/li>\n<\/ul>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Listing publication, reports, and preprints here to share pdf versions. Google Scholar: https:\/\/scholar.google.com\/citations?user=jQ4cGy0AAAAJ&amp;hl=en Publications &amp; Reports Keith Dillon, &#8220;Sources and Sinks in Functional Brain Networks&#8221;, Report 2025 (pdf) Keith Dillon, &#8220;Artificial Intelligence for Global Optimization of Blind 3D Reconstruction from<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages\/16"}],"collection":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/comments?post=16"}],"version-history":[{"count":46,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages\/16\/revisions"}],"predecessor-version":[{"id":458,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages\/16\/revisions\/458"}],"wp:attachment":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/media?parent=16"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}