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ORCIDMichael J. Healy
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2010 – 2019
- 2019
[j8]Michael J. Healy, Thomas P. Caudell:
Episodic memory: A hierarchy of spatiotemporal concepts. Neural Networks 120: 40-57 (2019)- 2018
- [j7]Michael J. Healy, Thomas P. Caudell:
Local and distributed concept representation via colimits: An example. Neurocomputing 314: 284-298 (2018) - 2012
- [c15]Shawn E. Taylor, Michael J. Healy, Thomas P. Caudell:
An Autonomous Distal Reward Learning Architecture for Embodied Agents. INNS-WC 2012: 198-204 - 2011
- [c14]Thomas P. Caudell, Cheir T. Burch, Mustafa Zengin, Nathan Gauntt, Michael J. Healy:
Retrospective learning of spatial invariants during object classification by embodied autonomous neural agents. IJCNN 2011: 2135-2142
2000 – 2009
- 2009
- [j6]Michael J. Healy, Richard D. Olinger, Robert J. Young, Shawn E. Taylor, Thomas P. Caudell, Kurt W. Larson:
Applying category theory to improve the performance of a neural architecture. Neurocomputing 72(13-15): 3158-3173 (2009) - [c13]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:
Memory in Silico: Building a Neuromimetic Episodic Cognitive Model. CSIE (5) 2009: 733-737 - [c12]Michael J. Healy, Thomas P. Caudell:
Temporal semantics: An extended definition for neural morphisms. IJCNN 2009: 1184-1191 - [c11]Shawn E. Taylor, Michael L. Bernard, Stephen J. Verzi, James D. Morrow, Craig M. Vineyard, Michael J. Healy, Thomas P. Caudell:
Temporal semantics: An Adaptive Resonance Theory approach. IJCNN 2009: 3111-3117 - 2007
- [c10]Shawn E. Taylor, Michael J. Healy, Thomas P. Caudell:
Categorical Mapping from Ontology to Neural Network: Initial Studies of Simple Neural Networks' Concept Capacity. IJCNN 2007: 2020-2025 - [c9]Dulany B. Weaver, Michael J. Healy, Thomas P. Caudell:
An Application of Category-Theoretic Design Methods to the Control of a Simulated Robot. IJCNN 2007: 2058-2063 - [c8]Robert J. Young, Mike Ritthaler, Peter Zimmer, John McGraw, Michael J. Healy, Thomas P. Caudell:
Comparison of Adaptive Resonance Theory Neural Networks for Astronomical Region of Interest Detection and Noise Characterization. IJCNN 2007: 2123-2128 - [p1]Michael J. Healy, Thomas P. Caudell:
Generalized Lattices Express Parallel Distributed Concept Learning. Computational Intelligence Based on Lattice Theory 2007: 59-77 - 2006
- [c7]Michael J. Healy, Thomas P. Caudell:
Generalized Lattices Express Parallel Distributed Concept Learning. FUZZ-IEEE 2006: 201-208 - [c6]Michael J. Healy, Thomas P. Caudell:
Knowledge Representation and Possible Worlds for Neural Networks. IJCNN 2006: 3047-3054 - 2003
- [j5]Thomas P. Caudell, Yunhai Xiao, Michael J. Healy:
eLoom and Flatland: specification, simulation and visualization engines for the study of arbitrary hierarchical neural architectures. Neural Networks 16(5-6): 617-624 (2003) - 2000
- [c5]Michael J. Healy:
Category Theory Applied to Neural Modeling and Graphical Representations. IJCNN (3) 2000: 35-40 - [c4]Stephen J. Verzi, Gregory L. Heileman, Michael Georgiopoulos, Michael J. Healy:
Hierarchical ARTMAP. IJCNN (6) 2000: 41-46
1990 – 1999
- 1999
- [j4]Michael J. Healy:
A Topological Semantics for Rule Extraction with Neural Networks. Connect. Sci. 11(1): 91-113 (1999) - [c3]Michael J. Healy:
Colimits in memory: category theory and neural systems. IJCNN 1999: 492-496 - [c2]Thomas P. Caudell, Michael J. Healy:
Studies of generalization for the LAPART-2 architecture. IJCNN 1999: 1979-1982 - 1998
- [j3]Michael J. Healy, Thomas P. Caudell:
Guaranteed two-pass convergence for supervised and inferential learning. IEEE Trans. Neural Networks 9(1): 195-204 (1998) - 1997
- [j2]Michael J. Healy, Thomas P. Caudell:
Acquiring rule sets as a product of learning in a logical neural architecture. IEEE Trans. Neural Networks 8(3): 461-474 (1997) - [c1]Gregory L. Heileman, Michael Georgiopoulos, Michael J. Healy, Stephen J. Verzi:
The generalization capabilities of ARTMAP. ICNN 1997: 1068-1071 - 1993
- [j1]Michael J. Healy, Thomas P. Caudell, Scott D. G. Smith:
A neural architecture for pattern sequence verification through inferencing. IEEE Trans. Neural Networks 4(1): 9-20 (1993)
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