scholarly journals Molecular Screening for Terahertz Detection with Machine-Learning-Based Methods

2021 ◽  
Vol 11 (4) ◽  
Author(s):  
Zsuzsanna Koczor-Benda ◽  
Alexandra L. Boehmke ◽  
Angelos Xomalis ◽  
Rakesh Arul ◽  
Charlie Readman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Screening ◽  
Terahertz Detection

scholarly journals MEMES: Machine learning framework for Enhanced MolEcular Screening

2021 ◽  
Author(s):  
Sarvesh Mehta ◽  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
Aaftaab Sethi ◽  
Mallika Alvala ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Screening ◽  
Learning Framework

scholarly journals Active learning and neural network potentials accelerate molecular screening of ether-based solvate ionic liquids

2020 ◽  
Vol 56 (63) ◽  
pp. 8920-8923 ◽  
Author(s):  
Wujie Wang ◽  
Tzuhsiung Yang ◽  
William H. Harris ◽  
Rafael Gómez-Bombarelli
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Ionic Liquids ◽  
Active Learning ◽  
Virtual Screening ◽  
Molecular Screening

Solvate ionic liquids (SIL) have promising applications as electrolyte materials and machine learning can help accelerate the virtual screening of candidate molecules for SIL.

scholarly journals MEMES: Machine learning framework for Enhanced MolEcular Screening

2021 ◽  
Author(s):  
Sarvesh Mehta ◽  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
Aaftaab Sethi ◽  
Mallika Alvala ◽  
...  
Keyword(s):  
Machine Learning ◽  
Drug Discovery ◽  
Virtual Screening ◽  
High Throughput ◽  
Molecular Screening ◽  
Learning Framework ◽  
High Throughput Virtual Screening

In drug discovery applications, high throughput virtual screening exercises are routinely performed to determine an initial set of candidate molecules referred to as "hits". In such an experiment, each molecule...

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Mathematics for Machine Learning

2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  
Machine Learning
Sign in / Sign up

Export Citation Format

Share Document