James W. Howse

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2ranked-venue papers

2as first author

0since 2021 · last 1998

—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence

1 paper

Deep learning architectures and training · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Machine learning › Deep learning architectures and training › training dynamics › optimization dynamics gradient dynamics	0.0	1	1995	Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks · NIPS 1995
Machine learning › Deep learning architectures and training training dynamics	0.0	1	1995	Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks · NIPS 1995

Methods — techniques the papers use, named apart from their topics

hamiltonian dynamics · 0.0gradient dynamics · 0.0

Year	Publication	Venue	Position
1998	A learning algorithm for applying synthesized stable dynamics to system identification James W. Howse, Chaouki T. Abdallah, Gregory L. Heileman	Neural Networks	1
1995	Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks James W. Howse, Chaouki T. Abdallah, Gregory L. Heileman	NIPS	1