From Hopfield nets to recursive networks to graph machines: Numerical machine learning for structured data-Reference-Cited by-同舟云学术

From Hopfield nets to recursive networks to graph machines: Numerical machine learning for structured data

Published:2005-11 Issue:2-3 Volume:344 Page:298-334
ISSN:0304-3975
Container-title:Theoretical Computer Science
language:en
Short-container-title:Theoretical Computer Science

Author:

Goulon-Sigwalt-Abram Aurélie,Duprat Arthur,Dreyfus Gérard

Publisher

Elsevier BV

Subject

General Computer Science,Theoretical Computer Science

Reference60 articles.

1. The principled design of large-scale recursive neural network architectures—DAG-RNNs and the protein structure prediction problem;Baldi;J. Mach. Learning Res.,2003

2. Application of cascade-correlation networks for structures to chemistry;Bianucci;Appl. Intelligence,2000

3. Elastic matching and pattern recognition in neural networks;Bienenstock,1989

4. A neural network for invariant pattern recognition;Bienenstock;Europhys. Lett.,1987

5. Neural Networks for Pattern Recognition;Bishop,1995

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Persistence of Correlations in Neurotransmitter Transport through the Synaptic Cleft;Biology;2024-07-18

2. Fast Prediction of the Equivalent Alkane Carbon Number Using Graph Machines and Neural Networks;ACS Omega;2022-10-18

3. Fast learning method for RAAM based on sensitivity analysis;SPIE Proceedings;2014-11-25

4. QSPR Prediction of the Stability Constants of Gadolinium(III) Complexes for Magnetic Resonance Imaging;Journal of Chemical Information and Modeling;2014-09-18

5. Graph Neural Networks for 3D Bravais Lattices Classification;Communications in Computer and Information Science;2014