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CONNECTIONIST LEARNING
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2024
Experts
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Daisuke Kimura
Moshe Y. Vardi
Jong-Hyeok Lee
Makoto Tatsuta
Artur S. d'Avila Garcez
Jude W. Shavlik
Jianlin Li
Gilles Barthe
Stefano Quer
Liqian Chen
Pengfei Yang
Gianpiero Cabodi
Xiaowei Huang
Carsten Schneider
Jiangchao Liu
Paolo Camurati
Shufang Zhu
Marco Gori
Stefan Wermter
Camil Demetrescu
Xiaoyu Song
Xuan Xie
Dominique Borrione
James R. Slagle
Koji Nakazawa
Maria L. Gini
Dean F. Hougen
Abolfazl Lavaei
Ugo Montanari
Forough Arabshahi
Geunbae Lee
Yongjian Li
Jan Oliver Ringert
William N. N. Hung
Sergey A. Gutnik
Forrest Brewer
Kristian Kersting
Filippo Bonchi
Lucas M. Tabajara
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Venues
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CoRR
J. Symb. Log.
SIGSAM Bull.
J. Symb. Comput.
ISSAC
IJCAI
NIPS
Artif. Intell.
Cogn. Sci.
Minds Mach.
CAV
Hybrid Neural Systems
DAC
Artif. Intell. Rev.
IJCNN
SYMSAC
Expert Syst. J. Knowl. Eng.
AISMC
Mach. Learn.
Neural Networks
ICLR
ICSE
AI Mag.
ICCD
Neurocomputing
ISMIR
IC-AI
Bull. Symb. Log.
Learning for Natural Language Processing
CEC
ICTAI
BIBE
Haifa Verification Conference
ICNN
CogSci
ECAI
ML
ICSLP
AMAST
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Related Topics
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systems biology
knowledge base
unit length
confidence values
manually annotated
information technology
sensitivity analysis
homology generators
analog vlsi
smart home
connectionist learning
coloured petri nets
associative memory
parameter selection
probabilistic model
artificial intelligence
multi modal
real world
morphological operators
monitoring system
text data
reactive planning
machine translation
probability distribution
traffic analysis
java programs
Related Keywords
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connectionist learning
connectionist models
neural learning
connectionist systems
machine learning
neural network
connectionist networks
reinforcement learning
associative learning
computer vision
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