default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDConnection Science, Volume 6
Volume 6, Number 1, 1994
- Valeriy I. Nenov, Michael G. Dyer:
Perceptually Grounded Language Learning: Part 2 - DETE: A Neural/Procedural Model. 3-41 - J. G. (Iain) Wallace, Richard B. Silberstein, Kevin Bluff, Andrew Pipingas:
Semantic Transparency, Brain Monitoring and Evaluation of Hybrid Cognitive Architectures. 43-58 - David R. Shanks, Mark A. Gluck:
Tests of an Adaptive Network Model for the Identification and Categorization of Continuous-dimension Stimuli. 59-89 - Omid M. Omidvar, Charles L. Wilson:
Information Content in Neural Net Optimization. 91-103
- Barak A. Pearlmutter
:
Simplifying Neural Network Soft Weight-sharing Measures by Soft Weight-measure Soft Weight Sharing. 105
- Stuart Jackson:
Human and Machine Thinking P. N. Johnson-Laird, 1993 Hillsdale, NJ: Lawrence Erlbaum AssociatesISBN 0-8058-0921, £19.95. 107-109
- Ronald L. Chrisley:
Conceptualizing How DETE Conceptualizes (or, 'More DETE-tales, Please!'). 113-115 - Georg Dorffner:
Why Connectionism and Language Modelling Need DETE. 115-118 - Terry Regier:
Sounds Good, Could You Elaborate on That? 119-120 - Stuart A. Jackson:
Grounding or Association? 120-122 - Michael G. Dyer, Valeriy I. Nenov:
Methodological Assumptions of DETE Project Revisited: Association-based Learning Requires Complex Architectures. 122-128
Volume 6, Numbers 2-3, 1994
- Niall Griffith, Peter Todd:
Editorial: Process and Representation in Connectionist Models of Musical Structure. 131-134 - Ian J. Taylor, Mike Greenhough:
Modelling Pitch Perception with Adaptive Resonance Theory Artificial Neural Networks. 135-154 - Niall Griffith:
Development of Tonal Centres and Abstract Pitch as Categorizations of Pitch Use. 155-176 - Edward W. Large, John F. Kolen:
Resonance and the Perception of Musical Meter. 177-208 - Stephen W. Smoliar:
Modelling Musical Perception: A Critical View. 209-222 - Michael P. A. Page:
Modelling the Perception of Musical Sequences with Self-organizing Neural Networks. 223-246 - Michael C. Mozer:
Neural Network Music Composition by Prediction: Exploring the Benefits of Psychoacoustic Constraints and Multi-scale Processing. 247-280 - Matthew I. Bellgard, Chi Ping Tsang:
Harmonizing Music the Boltzmann Way. 281-297 - Bruce F. Katz:
An Ear for Melody. 299-324 - Shumeet Baluja, Dean Pomerleau, Todd Jochem:
Towards Automated Artificial Evolution for Computer-generated Images. 325-354 - Michael A. Casey:
Understanding Musical Sound with Forward Models and Physical Models. 355-371
Volume 6, Number 4, 1994
- Garrison W. Cottrell, Kim Plunkett:
Acquiring the Mapping from Meaning to Sounds. 379-412 - Helen E. Moss, M. L. Hare, P. Day, Lorraine K. Tyler:
A Distributed Memory Model of the Associative Boost in Semantic Priming. 413-427 - Alessandro Sperduti:
Labelling Recursive Auto-associative Memory. 429-459 - David D. Vogel, William Boos:
Minimally Connective, Auto-associative, Neural Networks. 461-469 - Stuart A. Jackson:
A review of: "Neurons and Symbols: The Stuff That Mind is Made Of "I. Aleksander & H. Morton, 1993 London: Chapman & Hall. 471-473
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-12-04 01:28 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
