Alianna J. Maren Patents, Books, and Publications

• ResearcherID: P-4499-2014
• Google Scholar h-index: 10 (10/2017)

Alianna J. Maren Patents

• Patent Number 7,421,419 (September 2, 2008) System and Method for Evidence Accumulation and Hypothesis Generation
• Patent Number 7,389,282 (June 17, 2008) System and Method for Predictive analysis and Predictive Analysis Markup Language
• Patent Number 7,333,997 (February 19, 2008) Knowledge Discovery Method with Utility Functions and Feedback Loops; Knowledge Discovery Architecture.
• Patent Number 5,850,625 (December 15, 1998) Sensor Fusion Apparatus and Method; Selected by New York Times as a Patent of the Week. Sensor Fusion Patent: Overview and applications for biologically-inspired sensor fusion – a militarily critical technology.

Alianna J. Maren Book-in-Progress

“How can I develop a deep/unified view of statistical mechanics, information theory and machine learning?

“I learned all three fields independently (from physics, EE and cs), and many of the same concepts show up in all of them, some times with different meaning and views, like: entropy, maximum entropy model, Ising model, Boltzmann machine, partition function, information, energy, mean field, variational methods, phase transition, relative entropy, coding/decoding/inference, etc, etc. I felt that my understanding of those concepts are broken, lacking an unified view.” (Question posted on Quora.)

To answer that Quora-question, we need a book. Statistical Mechanics for Neural Networks and Artificial Intelligence: In Progress. Access the Overview, Précis, and More.

Journal Publications

• Maren, A.J. (2021). The 2-D Cluster Variation Method: Topography Illustrations and Their Enthalpy Parameter Correlations. Entropy,  23 (3), 319. doi:10.3390/e23030319. Available online at: https://doi.org/10.3390/e23030319. (Accessed Nov. 30, 2021.) Full text.
• Maren, A.J. (2016) The Cluster Variation Method: A Primer for Neuroscientists. Brain Sciences, 6(4), 44. doi:10.3390/brainsci6040044 pdf
• Maren, A.J., Pap, R.M., Priddy, K.L, & Akita, R.M. (1995). Neural network applications speed the Navy’s warfighting ability, Naval Research Review, 47 (3), 11-25. pdf
• Bulsara, A., Maren, A.J., & Schmera, G. (1993). Single effective neuron: dendritic coupling effects and stochastic resonance, Bio. Cybernetics 70 (2), 145-156. DOI: 10.1007/BF00200828 source
• Minsky, V., & Maren, A.J. (1990). “A multilayered, cooperative-competitive neural network for segmented scene analysis,” J. Neural Network Computing 1 (3) (Winter), 14-33.
• Maren, A.J., Lin, S.H., Langley, R.H., & Eyring, L. (1984). A theoretical model for hysteresis in solid state phase transitions, J. Solid State Chem., 53, 329-343. doi:10.1016/0022-4596(84)90110-5 pdf

arXiv Publications and Technical Reports

• Maren, A.J. (2019). Derivation of the variational Bayes equations. THM TR2019-001v4 (ajm). arXiv:1906.08804v4 [cs.NE] 30 Jul 2019. abstract; pdf.
• Maren, A.J. (2019). Free energy minimization using the 2-D cluster variation method: Initial code verification and validation. THM TR2018-001v2(ajm), arXiv:1801.08113v2 [cs.NE] 25 Jun 2019. abstract; pdf.
• Maren, A.J. (July, 2014) The Cluster Variation Method II: 2-D Grid of Zigzag Chains: Basic Theory, Analytic Solution and Free Energy Variable Distributions at Midpoint (x1 = x2 = 0.5). THM TR2014-003(ajm). DOI: 10.13140/2.1.4112.5446
• Maren, A.J. (June, 2014) The Cluster Variation Method I: 1-D Single Zigzag Chain: Basic Theory, Analytic Solution and Free Energy Variable Distributions at Midpoint (x1 = x2 = 0.5). THM TR2014-002(ajm). DOI: 10.13140/2.1.4415.6485
• Maren, A.J. (Feb., 2014) Statistical Thermodynamics: Introduction to Phase Space and Metastable States. THM TR2014-001(ajm).
• Maren, A.J. (Dec., 2013) Statistical Thermodynamics: Basic Theory and Equations. THM TR2013-001(ajm).

Books

• Maren, A.J. (writing as Alay’nya) (2011), Unveiling: The Inner Journey (McLean, VA: Mourning Dove Press).
• Maren, A.J., Harston, C.T., & Pap, R.M. (1990), Handbook of Neural Computing Applications (San Diego: Academic). DOI: 10.13140/2.1.2917.5364

YouTubes: Artificial Intelligence, Neural Networks, and Natural Language Processing (NLP)

Alianna J. Maren – YouTube

YouTubes: Themesis: Energy-Based Neural Networks and the Cluster Variation Method

Themesis Inc. – YouTube

Conference Publications

• Maren, A.J., & Szu, H. (2015). A new EEG measure using the 1-D Cluster Variation Method. SPIE STA (Sensing Technology + Applications) Conference: Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII (April 22, 2015, Baltimore, MD). DOI: 10.1117/12.2184651 pdf
• Maren, A.J., Donovan, D., Mathia, K., Robinson, T., & Saeks, R. (1997). New sensor fusion processor uses biological sensor fusion principles for advanced target correlation, IRIS National Symposium on Sensor and Data Fusion (MIT Lincoln Laboratory, Lexington, MA; April 14-17, 1997). (Distribution authorized to U.S. Government agencies only.) title half-page .
• Maren, A.J., Akita, R.M., Donovan, D., Mathia, K., Davis, J. (1997). Biological sensor fusion inspires novel sensor design, Joint Service Combat Identification Systems Conference (CISC-97, San Diego). source/pdf
• Saeks, R.E., Cox, C.J., Mathia, K., Maren, A.J. (1997). Asymptotic dynamic programming: preliminary concepts and results. Proc. Int’l. Conf. Neural Networks (Volume:4 ) (9-12 Jun 1997, Houston, TX), 2273 – 2278. DOI 10.1109/ICNN.1997.614399 source pdf
• Maren, A.J. (1995). Neural networks for intelligent agents: a new horizon. World Congress on Neural Networks (WCNN’95) (Washington, D.C., July 17-21, 1995). pdf.
• Maren, A.J. (1993). Neural Networks for Intelligent Agents (Extended Abstract), IEEE SMC Conference (1993).
• Maren, A.J. (1993). Free energy as driving function in neural networks. 1993 Symposium on Nonlinear Theory and Its Applications (Hawaii: Dec. 5-10, 1993). DOI 10.13140/2.1.1621.1529 pdf
• Bulsara, A., & Maren, A.J. (1993). Coupled neural-dendritic processes: cooperative stochastic effects and the analysis of spike trains, in Rethinking Neural Networks: Quantum Fields and Biological Data, selected proceedings of the First Appalachian Conference on Neurodynamics, Radford University, 1992. (Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. & INNS).
• Schwartz, E. & Maren, A.J. (1993). Domains of Interacting Neurons: A Statistical Thermodynamics Model, World Congress on Neural Networks (WCNN’93 – Portland), (Portland, OR: July 11-15, 1993), I-577 – I-580.
• Maren, A.J., Lothers, M.D., Pap, R.M., & Akita, R. (1992). Neural network sensor data fusion methods for naval air traffic control, Proc. Navy SBIR Neural Network Conference (Arlington, VA: June 4-5, 1992), 109-116. doi:10.13140/RG.2.1.5178.3526 pdf
• Maren, A.J., Schwartz, E., & Seyfried, J. (1992). Configurational Entropy Stabilizes Pattern Formation in a Hetero-Associative Neural Network, 1992 IEEE International Conference on Systems, Man, & Cybernetics (Chicago, Il: Oct. 18-21, 1992), 89-93. DOI: 10.1109/ICSMC.1992.271796 pdf.
• Maren, A.J. (1991). A logical topology of neural networks, Proceedings of the Second Workshop in Neural Networks – Academia, Industry, NASA, & Defense (WNN-AIND 91) (Auburn, GA; Feb. 14-16, 1991). doi:10.13140/RG.2.1.3503.2806 pdf
• Maren, A.J. (1991). Neural networks for enhanced human-computer interactions. IEEE Control Systems Magazine 11(5) (Aug, 1991) 34-36. doi:10.1109/37.90537 pdf
• Pap, R.M., Harston, C.T., Maren, A.J., Parten, C.R., Rich, M.L., & Akita, R.M. (1990). Neural network implementation of multisensory fusion for target identification problems (1990). 3rd National Sensor Fusion Conference. (Distribution authorized to U.S. Government agencies only.) title half-page .
• Maren, A.J. (1989). A Hierarchical Data Structure Representation for Fusing Multisensor Information, Sensor Fusion II, Proc. SPIE VoL 1100, March 1989, pp. 162-ff.
• Maren, A.J. (1988). The IEEE 1st International Conference on Neural Networks – a first-hand account, SIGART Newsletter, Number 103, (January 1988) 27-29.
• Maren, A.J., Ali, M. (1988). Hierarchical Scene Structure Representations to Facilitate Image Understanding, IEA/AIE (Vol. 2) 1988 : 657-667.

Workshop Reports

• Maren, A.J., & Lesgold, A. (1991). Enhanced Human-Computer Interfaces: A Multi-Disciplinary Approach, Report to the National Science Foundation (Washington, DC, 1991).

Technology Magazine Publications

• Maren, A.J. (2017), How GPUs, AI, and Deep Learning Make Smart Products Smarter, Product Design & Development, September-October017, pp. 18-21. online access, extended version Part 1 with links to the full reference list, and extended version Part 2 with links to the full reference list.
• Maren, A.J. (2017), Designing Like It’s 2025: Next-Gen CAD Technologies Give Designers “Awesome Superpowers,” Product Design & Development, July-August, 2017, pp. 14-17. online access.
• Goldberg, L., Crouse, M., and Maren, A.J. (2016), Artificial Intelligence Invades Consumer Electronics, Product Design & Development, September, 2016, pp. 10-13. online access.

Workshop Organization and Participation

• Workshop on Collaborative Research into Learning and Intelligent Systems (1995). Member – Learner-System Interaction Breakout Group. Sponsored by the National Science Foundation (Washington, DC, 1995).
• World Congress on Neural Networks (1995). Program Committee (Washington, D.C., July 17-21, 1995).
• Maren, A.J. (1991). Neural Networks for Enhanced Human-Computer Interactions, Workshop on Neural Networks: Academia/Industry/NASA/Defense (Auburn, AL, Feb. 11-13, 1991), and reprinted in IEEE Control Systems, 1991, 34-36. DOI: 10.1109/37.90537 pdf.

Short Courses

• Maren, A.J., Leven, S., & Briggs, A.B.. (1995). Neural networks to advance intelligent systems: A New Frontier, Presented at WCNN’95: World Congress on Neural Networks (Washington, D.C., July 17-21, 1995).

White Papers (Old)

• Maren, A.J. (1989). A Tutorial on the Boltzmann Distribution and Energy Minimization for Neural Network Ensembles, White Paper, University of Tennessee Space Institute. DOI: 10.13140/2.1.3044.7685

Industry Technical Reports (Submitted to Government Agencies)

• Heazel, C., & Maren, A.J. (2004). Net-Centric Enterprise Services (NCES) 2nd Working Group: Mediation and Discovery: March 5, 2004 Status Report, Arlington, VA, 2004.
• Harrison, J., Maren, A.J., et al. (2004). Enterprise Architecture Special Interest Group(EA-SIG) Discovery Working Group: Discovery within the GIG Enterprise Services and Including a Discussion of Enterprise Architecture Patterns February 20, 2004, Arlington, VA, 2004.
• Maren, A.J. et al. (2004). Final Report for Predictive Analysis – Market Survey and Assessment, submitted to DoDIIS Innovation (DIA Research and Requirements Branch).
• Maren, A.J. et al. (1997). Final Report for Biological Sensor Fusion, Phase II STTR N00014-95-C-0323 “Signal Processing Chips/Electronics,” submitted to ONR (Office of Naval Research).
• Uhrig, R.E., &Maren, A.J. (1989). Enhancing Nuclear Power Plant Performance Through the Use of Artificial Intelligence: First Annual Report, Department of Energy Contract #DE-FG07-88ER12824, June 15, 1989, Dept. of Nuclear Engineering, University of Tennessee, Knoxville, TN.

Reviewer for Journals

• Entropy, see Publons for listing of reviews,
• Frontiers in Systems Neuroscience
  • Kozma & Freeman, Cinematic Operation of the Cerebral Cortex Interpreted via Critical Transitions in Self-Organized Dynamic Systems
  • N. Newton, Understanding and Self-Organization

Recent Talks

• What Outreach Mechanisms Does Your Business Need? Tuesday, February 18th, LITE (Laboratory for IT Entrepreneurship), George Mason University. 12 Noon – 1PM. full event flyer with abstract here.
• Social Entrepreneurship & Building Tribal Connections, Association of IT Professionals (Washington DC Chapter, April 11, 2013).

Alianna J. Maren – Work-in-Progress

• Maren, A.J. (2016) Brain-Based Computing (PPT). PPT
• Maren, A.J. (2015) How the Brain Solves Tough Problems. In Making Sense: Extracting Meaning from Text by
  Matching Entities and Terms to Ontologies and Concepts, pdf