Fuzzy Set Methods for Assessing Uncertainty in the Modeling and Control of Space Structures. - Timothy J. Ross; T. K. Hasselman; J. D. Chrostowski; Stephen J. Verzi (J. Intell. Fuzzy Syst., 1993)

The generalization capabilities of ARTMAP. - Gregory L. Heileman; Michael Georgiopoulos; Michael J. Healy; Stephen J. Verzi (ICNN, 1997)

Hierarchical ARTMAP. - Stephen J. Verzi; Gregory L. Heileman; Michael Georgiopoulos; Michael J. Healy (IJCNN (6), 2000)

Exemplar-based pattern recognition via semi-supervised learning. - Gregorios C. Anagnostopoulos; Madan Bharadwaj; Michael Georgiopoulos; Stephen J. Verzi; Gregory L. Heileman (IJCNN, 2003)

Universal approximation with Fuzzy ART and Fuzzy ARTMAP. - Stephen J. Verzi; Gregory L. Heileman; Michael Georgiopoulos; Georgios C. Anagnostopoulos (IJCNN, 2003)

Boosted ARTMAP: Modifications to fuzzy ARTMAP motivated by boosting theory. - Stephen J. Verzi; Gregory L. Heileman; Michael Georgiopoulos (Neural Networks, 2006)

Preparing for the aftermath: Using emotional agents in game-based training for disaster response. - Donna Djordjevich; Patrick G. Xavier; Michael L. Bernard; Jonathan Whetzel; Matthew R. Glickman; Stephen J. Verzi (CIG, 2008)

Memory in Silico: Building a Neuromimetic Episodic Cognitive Model. - Shawn E. Taylor; Craig M. Vineyard; Michael J. Healy; Thomas P. Caudell; Neal J. Cohen; Patrick D. Watson; Stephen J. Verzi; J. Daniel Morrow; Michael L. Bernard; Howard Eichenbaum (CSIE (5), 2009)

Temporal semantics: An Adaptive Resonance Theory approach. - Shawn E. Taylor; Michael L. Bernard; Stephen J. Verzi; James D. Morrow; Craig M. Vineyard; Michael J. Healy; Thomas P. Caudell (IJCNN, 2009)

A Neurologically Plausible Artificial Neural Network Computational Architecture of Episodic Memory and Recall. - Craig M. Vineyard; Michael L. Bernard; Shawn E. Taylor; Thomas P. Caudell; Patrick D. Watson; Stephen J. Verzi; Neal J. Cohen; Howard Eichenbaum (BICA, 2010)

A Multimodal Hypertensor Architecture for Association Formation. - Craig M. Vineyard; Stephen J. Verzi; Michael L. Bernard; Thomas P. Caudell (BICA, 2011)

A neurophysiologically inspired hippocampus based associative-ART Artificial neural network architecture. - Craig M. Vineyard; Stephen J. Verzi; Michael L. Bernard; Shawn E. Taylor; Wendy L. Shaneyfelt; Irene Dubicka; Jonathan T. McClain; Thomas P. Caudell (IJCNN, 2011)

An information-theoretic, vector-space-model approach to cross-language information retrieval. - Peter A. Chew; Brett W. Bader; Stephen Helmreich; Ahmed Abdelali; Stephen J. Verzi (Nat. Lang. Eng., 2011)

A Game Theoretic Model of Neurocomputation. - Craig M. Vineyard; Glory R. Emmanuel; Stephen J. Verzi; Gregory L. Heileman (BICA, 2012)

Game theoretic mechanism design applied to machine learning classification. - Craig M. Vineyard; Gregory L. Heileman; Stephen J. Verzi; Ramiro Jordan (CIP, 2012)

The Impact of Attitude Resolve on Population Wide Attitude Change. - Craig M. Vineyard; Kiran Lakkaraju; Joseph Collard; Stephen J. Verzi (SBP, 2012)

A multi-modal network architecture for knowledge discovery. - Craig M. Vineyard; Stephen J. Verzi; Michael L. Bernard; Shawn E. Taylor; Irene Dubicka; Thomas P. Caudell (Secur. Informatics, 2012)

Adult Neurogenesis: Implications on Human And Computational Decision Making. - Craig M. Vineyard; Stephen J. Verzi; Thomas P. Caudell; Michael L. Bernard; James B. Aimone (HCI (24), 2013)

Repeated play of the SVM game as a means of adaptive classification. - Craig M. Vineyard; Stephen J. Verzi; Conrad D. James; James B. Aimone; Gregory L. Heileman (IJCNN, 2015)

MapReduce SVM Game. - Craig M. Vineyard; Stephen J. Verzi; Conrad D. James; James B. Aimone; Gregory L. Heileman (INNS Conference on Big Data, 2015)

Simulating smoking behaviors based on cognition-determined, opinion-based system dynamics. - Asmeret Bier Naugle; Nadine E. Miner; Munaf Aamir; Robert Jeffers; Stephen J. Verzi; Michael L. Bernard (WSC, 2015)

Overcoming the Static Learning Bottleneck - the need for adaptive neural learning. - Craig M. Vineyard; Stephen J. Verzi (ICRC, 2016)

Quantifying neural information content: A case study of the impact of hippocampal adult neurogenesis. - Craig M. Vineyard; Stephen J. Verzi; Conrad D. James; James B. Aimone (IJCNN, 2016)

A Spike-Timing Neuromorphic Architecture. - Aaron J. Hill; Jonathon W. Donaldson; Fredrick H. Rothganger; Craig M. Vineyard; David R. Follett; Pamela L. Follett; Michael R. Smith 002; Stephen J. Verzi; William Severa; Felix Wang; James B. Aimone; John H. Naegle; et al. (ICRC, 2017)

Optimization-based computation with spiking neurons. - Stephen J. Verzi; Craig M. Vineyard; Eric D. Vugrin; Meghan A. Galiardi; Conrad D. James; James B. Aimone (IJCNN, 2017)

Physical Security Assessment Using Temporal Machine Learning. - Meghan A. Galiardi; Stephen J. Verzi; Gabriel C. Birch; Jaclynn J. Stubbs; Bryana L. Woo; Camron G. Kouhestani (ICCST, 2018)

Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication. - William Severa; Craig M. Vineyard; Ryan Dellana; Stephen J. Verzi; James B. Aimone (CoRR, 2018)

Computing with Spikes: The Advantage of Fine-Grained Timing. - Stephen J. Verzi; Fredrick H. Rothganger; Ojas Parekh; Tu-Thach Quach; Nadine E. Miner; Craig M. Vineyard; Conrad D. James; James B. Aimone (Neural Comput., 2018)

Training deep neural networks for binary communication with the Whetstone method. - William Severa; Craig M. Vineyard; Ryan Dellana; Stephen J. Verzi; James B. Aimone (Nat. Mach. Intell., 2019)

Permeability Prediction of Porous Media using Convolutional Neural Networks with Physical Properties. - Hongkyu Yoon; Darryl J. Melander; Stephen J. Verzi (AAAI Spring Symposium: MLPS, 2020)

Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis. - Michael R. Smith 002; Nicholas T. Johnson; Joe B. Ingram; Armida J. Carbajal; Bridget I. Haus; Eva Domschot; Ramyaa; Christopher C. Lamb; Stephen J. Verzi; W. Philip Kegelmeyer (AISec@CCS, 2020)

Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security. - Michael R. Smith 002; Nicholas T. Johnson; Joe B. Ingram; Armida J. Carbajal; Ramyaa Ramyaa; Evelyn Domschot; Christopher C. Lamb; Stephen J. Verzi; W. Philip Kegelmeyer (CoRR, 2020)

Machine Learning Application for Permeability Estimation of Three-Dimensional Rock Images. - Hongkyu Yoon; Darryl J. Melander; Stephen J. Verzi (AAAI Spring Symposium: MLPS, 2021)

Malware Generation with Specific Behaviors to Improve Machine Learning-based Detection. - Michael R. Smith 002; Stephen J. Verzi; Nicholas T. Johnson; Xin Zhou; Kanad Khanna; Sophie Quynn; Raga Krishnakumar (IEEE BigData, 2021)

Conflicting Information and Compliance with COVID-19 Behavioral Recommendations. - Asmeret Bier Naugle; Fred Rothganger; Stephen J. Verzi; Casey Doyle (J. Artif. Soc. Soc. Simul., 2022)

A Theoretical Approach for Reliability Within Information Supply Chains With Cycles and Negations. - Michael Livesay; Daniel Pless; Stephen J. Verzi; Kevin Stamber; Anneliese Lilje (IEEE Trans. Reliab., 2022)

Efficient machine-learning surrogates for large-scale geological carbon and energy storage. - Teeratorn Kadeethum; Stephen J. Verzi; Hongkyu Yoon (CoRR, 2023)

Feedback density and causal complexity of simulation model structure. - Asmeret Naugle; Stephen J. Verzi; Kiran Lakkaraju; Laura P. Swiler; Christina Warrender; Michael L. Bernard; Vicente J. Romero (J. Simulation, 2023)

What can simulation test beds teach us about social science? Results of the ground truth program. - Asmeret Bier Naugle; Daniel Krofcheck; Christina Warrender; Kiran Lakkaraju; Laura Painton Swiler; Stephen J. Verzi; Ben Emery; Jaimie Murdock; Michael L. Bernard; Vicente J. Romero (Comput. Math. Organ. Theory, 2023)

The Ground Truth program: simulations as test beds for social science research methods. - Asmeret Bier Naugle; Adam Russell; Kiran Lakkaraju; Laura Painton Swiler; Stephen J. Verzi; Vicente J. Romero (Comput. Math. Organ. Theory, 2023)