Machine Learning-Guided Discovery of Underlying Decisive Factors and New Mechanisms for the Design of Nonprecious Metal Electrocatalysts

ACS Catalysis ◽  
2021 ◽  
pp. 9798-9808
Author(s):  
Rui Ding ◽  
Yawen Chen ◽  
Ping Chen ◽  
Ran Wang ◽  
Jiankang Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Guided Discovery ◽  
Nonprecious Metal

Machine-Learning-Guided Discovery and Optimization of Additives in Preparing Cu Catalysts for CO2 Reduction

2021 ◽  
Vol 143 (15) ◽  
pp. 5755-5762
Author(s):  
Ying Guo ◽  
Xinru He ◽  
Yuming Su ◽  
Yiheng Dai ◽  
Mingcan Xie ◽  
...  
Keyword(s):  
Machine Learning ◽  
Co2 Reduction ◽  
Guided Discovery ◽  
Cu Catalysts

Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis

2021 ◽  
Author(s):  
Marcus Reis ◽  
Filipp Gusev ◽  
Nicholas G. Taylor ◽  
Sang Hun Chung ◽  
Matthew D. Verber ◽  
...  
Keyword(s):  
Machine Learning ◽  
Guided Discovery ◽  
19F Mri

Machine learning guided discovery of super-hard high entropy ceramics

2021 ◽  
pp. 130899
Author(s):  
Russlan Jaafreh ◽  
Yoo Seong Kang ◽  
Jung-Gu Kim ◽  
Kotiba Hamad
Keyword(s):  
Machine Learning ◽  
Guided Discovery ◽  
High Entropy

scholarly journals Machine-learning-guided discovery of the gigantic magnetocaloric effect in HoB2 near the hydrogen liquefaction temperature

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Pedro Baptista de Castro ◽  
Kensei Terashima ◽  
Takafumi D Yamamoto ◽  
Zhufeng Hou ◽  
Suguru Iwasaki ◽  
...  
Keyword(s):  
Machine Learning ◽  
Magnetocaloric Effect ◽  
Guided Discovery ◽  
Liquefaction Temperature

scholarly journals Machine Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis

2021 ◽  
Author(s):  
Marcus Reis ◽  
Filipp Gusev ◽  
Nicolas Taylor ◽  
Sang Hun Chung ◽  
Matthew Verber ◽  
...  
Keyword(s):  
Machine Learning ◽  
Guided Discovery ◽  
19F Mri

scholarly journals Machine-learning guided discovery of a new thermoelectric material

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yuma Iwasaki ◽  
Ichiro Takeuchi ◽  
Valentin Stanev ◽  
Aaron Gilad Kusne ◽  
Masahiko Ishida ◽  
...  
Keyword(s):  
Machine Learning ◽  
Thermoelectric Material ◽  
Guided Discovery

scholarly journals AMPGAN v2: Machine Learning Guided Discovery of Anti-Microbial Peptides

2020 ◽  
Author(s):  
Colin M. Van Oort ◽  
Jonathon B. Ferrell ◽  
Jacob M. Remington ◽  
Safwan Wshah ◽  
Jianing Li
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Public Health Problem ◽  
Design Tool ◽  
Data Driven ◽  
Generative Adversarial Network ◽  
Guided Discovery ◽  
Adversarial Network ◽  
Critical Public Health ◽  
The U.S

AbstractAntibiotic resistance is a critical public health problem. Each year ~2.8 million resistant infections lead to more than 35,000 deaths in the U.S. alone. Anti-microbial peptides (AMPs) show promise in treating resistant infections. But, applications of known AMPs have encountered issues in development, production, and shelf-life. To drive the development of AMPbased treatments it is necessary to create design approaches with higher precision and selectivity towards resistant targets.In this paper we present AMPGAN v2, a generative adversarial network (GAN) based approach for rational AMP design. Like AMP-GAN,1 AMPGAN v2 combines data driven priors and controlled generation. These elements allow for the generation of AMP candidates tailored for specific applications. AMPGAN v2 is able to generate AMP candidates that are novel and diverse, making it an efficient AMP design tool.

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
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