Predicting phosphorus nuclear magnetic resonance (NMR) shifts using neural networks. 3. Element-value optimizing (EVO) network architectures

1995 ◽  
Vol 35 (5) ◽  
pp. 806-814 ◽  
Author(s):  
Geoffrey M. J. West
Keyword(s):  
Neural Networks ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Network Architectures ◽  
Nuclear Magnetic

Neural networks for the peak-picking of nuclear magnetic resonance spectra

1993 ◽  
Vol 6 (7) ◽  
pp. 1023-1032 ◽  
Author(s):  
Enrico A. Carrara ◽  
Franco Pagliari ◽  
Claudio Nicolini
Keyword(s):  
Neural Networks ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Peak Picking ◽  
Nuclear Magnetic Resonance Spectra ◽  
Magnetic Resonance Spectra ◽  
Nuclear Magnetic

scholarly journals Predicting Chemical Shifts with Graph Neural Networks

2021 ◽  
Author(s):  
Ziyue Yang ◽  
Maghesree Chakraborty ◽  
Andrew D White
Keyword(s):  
Molecular Structure ◽  
Neural Networks ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Chemical Shifts ◽  
3D Structure ◽  
Forward Model ◽  
Forward Models ◽  
Graph Neural Networks ◽  
Nuclear Magnetic

Inferring molecular structure from Nuclear Magnetic Resonance (NMR) measurements requires an accurate forward model that can predict chemical shifts from 3D structure. Current forward models are limited to specific molecules...

scholarly journals Predicting Octane Number Using Nuclear Magnetic Resonance Spectroscopy and Artificial Neural Networks

2018 ◽  
Vol 32 (5) ◽  
pp. 6309-6329 ◽  
Author(s):  
Abdul Gani Abdul Jameel ◽  
Vincent Van Oudenhoven ◽  
Abdul-Hamid Emwas ◽  
S. Mani Sarathy
Keyword(s):  
Neural Networks ◽  
Nuclear Magnetic Resonance ◽  
Artificial Neural Networks ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Nuclear Magnetic Resonance Spectroscopy ◽  
Octane Number ◽  
Resonance Spectroscopy ◽  
Artificial Neural ◽  
Nuclear Magnetic
Sign in / Sign up

Export Citation Format

Share Document