Michael J. Healy - researchr alias

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Viewing Publication 1 - 24 from 24

2019

Episodic memory: A hierarchy of spatiotemporal conceptsMichael J. Healy, Thomas P. Caudell. NN, 120:40-57, 2019. [doi]

2018

Local and distributed concept representation via colimits: An exampleMichael J. Healy, Thomas P. Caudell. ijon, 314:284-298, 2018. [doi]

2012

An Autonomous Distal Reward Learning Architecture for Embodied AgentsShawn E. Taylor, Michael J. Healy, Thomas P. Caudell. procedia, 13:198-204, 2012. [doi]

2011

Retrospective learning of spatial invariants during object classification by embodied autonomous neural agentsThomas P. Caudell, Cheir T. Burch, Mustafa Zengin, Nathan Gauntt, Michael J. Healy. ijcnn 2011: 2135-2142 [doi]

2009

2007

Generalized Lattices Express Parallel Distributed Concept LearningMichael J. Healy, Thomas P. Caudell. In Vassilis G. Kaburlasos, Gerhard X. Ritter, editors, Computational Intelligence Based on Lattice Theory. Volume 67 of Studies in Computational Intelligence, pages 59-77, Springer, 2007. [doi]

Categorical Mapping from Ontology to Neural Network: Initial Studies of Simple Neural Networks Concept CapacityShawn E. Taylor, Michael J. Healy, Thomas P. Caudell. ijcnn 2007: 2020-2025 [doi]

An Application of Category-Theoretic Design Methods to the Control of a Simulated RobotDulany B. Weaver, Michael J. Healy, Thomas P. Caudell. ijcnn 2007: 2058-2063 [doi]

Comparison of Adaptive Resonance Theory Neural Networks for Astronomical Region of Interest Detection and Noise CharacterizationRobert J. Young, Mike Ritthaler, Peter Zimmer, John McGraw, Michael J. Healy, Thomas P. Caudell. ijcnn 2007: 2123-2128 [doi]

2006

Knowledge Representation and Possible Worlds for Neural NetworksMichael J. Healy, Thomas P. Caudell. ijcnn 2006: 3047-3054 [doi]

Generalized Lattices Express Parallel Distributed Concept LearningMichael J. Healy, Thomas P. Caudell. fuzzIEEE 2006: 201-208 [doi]

2003

eLoom and Flatland: specification, simulation and visualization engines for the study of arbitrary hierarchical neural architecturesThomas P. Caudell, Yunhai Xiao, Michael J. Healy. NN, 16(5-6):617-624, 2003. [doi]

2000

Category Theory Applied to Neural Modeling and Graphical RepresentationsMichael J. Healy. ijcnn 2000: 35-40 [doi]

Hierarchical ARTMAPStephen J. Verzi, Gregory L. Heileman, Michael Georgiopoulos, Michael J. Healy. ijcnn 2000: 41-46 [doi]

1999

Studies of generalization for the LAPART-2 architectureThomas P. Caudell, Michael J. Healy. ijcnn 1999: 1979-1982 [doi]

A Topological Semantics for Rule Extraction with Neural NetworksMichael J. Healy. connection, 11(1):91-113, 1999. [doi]

Colimits in memory: category theory and neural systemsMichael J. Healy. ijcnn 1999: 492-496 [doi]

1998

Guaranteed two-pass convergence for supervised and inferential learningMichael J. Healy, Thomas P. Caudell. tnn, 9(1):195-204, 1998. [doi]

1997

Acquiring rule sets as a product of learning in a logical neural architectureMichael J. Healy, Thomas P. Caudell. tnn, 8(3):461-474, 1997. [doi]

The generalization capabilities of ARTMAPGregory L. Heileman, Michael Georgiopoulos, Michael J. Healy, Stephen J. Verzi. icnn 1997: 1068-1071 [doi]

1993

A neural architecture for pattern sequence verification through inferencingMichael J. Healy, Thomas P. Caudell, Scott D. G. Smith. tnn, 4(1):9-20, 1993. [doi]

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