Mapping Part-Whole Hierarchies into Connectionist Networks
暂无分享,去创建一个
[1] Geoffrey E. Hinton. Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems , 1991 .
[2] David S. Touretzky,et al. BoltzCONS: Dynamic Symbol Structures in a Connectionist Network , 1990, Artif. Intell..
[3] Jordan B. Pollack,et al. Recursive Distributed Representations , 1990, Artif. Intell..
[4] Geoffrey E. Hinton,et al. Distributed Representations , 1986, The Philosophy of Artificial Intelligence.
[5] W. Freeman. Second Commentary: On the proper treatment of connectionism by Paul Smolensky (1988) - Neuromachismo Rekindled , 1989 .
[6] Geoffrey E. Hinton. Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space , 1989, Neural Computation.
[7] Geoffrey E. Hinton. Learning distributed representations of concepts. , 1989 .
[8] L. Shastri,et al. A Connectionist System for Rule Based Reasoning With Multi-Place Predicates and Variables , 1989 .
[9] J. Fodor,et al. Connectionism and cognitive architecture: A critical analysis , 1988, Cognition.
[10] P. Smolensky. On the proper treatment of connectionism , 1988, Behavioral and Brain Sciences.
[11] James L. McClelland,et al. An interactive activation model of context effects in letter perception: part 1.: an account of basic findings , 1988 .
[12] James L. McClelland,et al. James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.
[13] Mark Derthick. Counterfactual Reasoning with Direct Models , 1987, AAAI.
[14] Fernando J. Pineda,et al. Generalization of Back propagation to Recurrent and Higher Order Neural Networks , 1987, NIPS.
[15] Geoffrey E. Hinton. Using fast weights to deblur old memories , 1987 .
[16] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[17] James L. McClelland. The programmable blackboard model of reading , 1986 .
[18] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[19] D. Rumelhart. Learning internal representations by back-propagating errors , 1986 .
[20] Geoffrey E. Hinton,et al. Symbols Among the Neurons: Details of a Connectionist Inference Architecture , 1985, IJCAI.
[21] Geoffrey E. Hinton,et al. Shape Recognition and Illusory Conjunctions , 1985, IJCAI.
[22] W. Daniel Hillis,et al. The connection machine , 1985 .
[23] Paul Smolensky,et al. Schema Selection and Stochastic Inference in Modular Environments , 1983, AAAI.
[24] David H. Ackley,et al. The QBKG System: Generating Explanations From a Non-Discrete Knowledge Representation , 1982, AAAI.
[25] J J Hopfield,et al. Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.
[26] James L. McClelland,et al. An interactive activation model of context effects in letter perception: I. An account of basic findings. , 1981 .
[27] Scott E. Fahlman,et al. NETL: A System for Representing and Using Real-World Knowledge , 1979, CL.
[28] Teuvo Kohonen,et al. Associative memory. A system-theoretical approach , 1977 .
[29] H B Barlow,et al. Single units and sensation: a neuron doctrine for perceptual psychology? , 1972, Perception.
[30] H. C. LONGUET-HIGGINS,et al. Non-Holographic Associative Memory , 1969, Nature.
[31] Arthur L. Samuel,et al. Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..