reviewTop 10% cited
Catastrophic forgetting in connectionist networks
Trends in Cognitive Sciences · 1999 · Vol. 3(4) · pp. 128–135
Robert M. French✉(University of Liège)R French(University of Liège)
Neural Networks and ApplicationsDomain Adaptation and Few-Shot LearningCognitive Science and Education ResearchForgettingConnectionismCognitionCognitive scienceArtificial neural networkComputer scienceCognitive systemsNatural (archaeology)Artificial intelligencePsychology
Citations
2,228
FWCI
10.96
field-weighted impact
References
50
Percentile
98%
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Citations per year
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References
Learning representations by back-propagating errors
Nature · 1986 · 30,045 citations
The perceptron: A probabilistic model for information storage and organization in the brain.
Psychological Review · 1958 · 11,537 citations
Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory.
Psychological Review · 1995 · 5,292 citations
Scalar Timing in Memory
Annals of the New York Academy of Sciences · 1984 · 1,782 citations
Principles of Neurodynamics.
American Mathematical Monthly · 1963 · 2,222 citations
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Catastrophic forgetting in connectionist networks
Trends in Cognitive Sciences · 1999 · 2,228 citations
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