Michael J. Healy

	2011
15		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
	2009
14		Shawn E. Taylor, Craig M. Vineyard, Michael J. Healy, Thomas P. Caudell, Neal J. Cohen, Patrick 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
13		Michael J. Healy, Thomas P. Caudell: Temporal semantics: An extended definition for neural morphisms. IJCNN 2009: 1184-1191
12		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
11		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)
	2007
10		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
9		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
8		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
7		Michael J. Healy, Thomas P. Caudell: Generalized Lattices Express Parallel Distributed Concept Learning. Computational Intelligence Based on Lattice Theory 2007: 59-77
	2006
6		Michael J. Healy, Thomas P. Caudell: Knowledge Representation and Possible Worlds for Neural Networks. IJCNN 2006: 3047-3054
	2003
5		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
4		Michael J. Healy: Category Theory Applied to Neural Modeling and Graphical Representations. IJCNN (3) 2000: 35-40
3		Stephen J. Verzi, Gregory L. Heileman, Michael Georgiopoulos, Michael J. Healy: Hierarchical ARTMAP. IJCNN (6) 2000: 41-46
	1999
2		Michael J. Healy: A Topological Semantics for Rule Extraction with Neural Networks. Connect. Sci. 11(1): 91-113 (1999)
	1998
1		Michael J. Healy, Thomas P. Caudell: Guaranteed two-pass convergence for supervised and inferential learning. IEEE Transactions on Neural Networks 9(1): 195-204 (1998)

Coauthor Index

1	Michael L. Bernard	[12] [14]
2	Cheir T. Burch	[15]
3	Thomas P. Caudell	[1] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15]
4	Neal J. Cohen	[14]
5	Howard Eichenbaum	[14]
6	Nathan Gauntt	[15]
7	Michael Georgiopoulos	[3]
8	Gregory L. Heileman	[3]
9	Kurt W. Larson	[11]
10	John McGraw	[8]
11	J. Daniel Morrow	[14]
12	James D. Morrow	[12]
13	Richard D. Olinger	[11]
14	Mike Ritthaler	[8]
15	Shawn E. Taylor	[10] [11] [12] [14]
16	Stephen J. Verzi	[3] [12] [14]
17	Craig M. Vineyard	[12] [14]
18	Patrick Watson	[14]
19	Dulany B. Weaver	[9]
20	Yunhai Xiao	[5]
21	Robert J. Young	[8] [11]
22	Mustafa Zengin	[15]
23	Peter Zimmer	[8]

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