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Duan, Chenru
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1
New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts
由
Nandy, Aditya
,
Duan, Chenru
,
Goffinet, Conrad
,
Kulik, Heather J.
出版 2022
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Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization
由
Janet, Jon Paul
,
Ramesh, Sahasrajit
,
Duan, Chenru
,
Kulik, Heather J.
出版 2020
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3
Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost
由
Duan, Chenru
,
Chu, Daniel B. K.
,
Nandy, Aditya
,
Kulik, Heather J.
出版 2022
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4
A quantitative uncertainty metric controls error in neural network-driven chemical discovery
由
Janet, Jon Paul
,
Duan, Chenru
,
Yang, Tzuhsiung
,
Nandy, Aditya
,
Kulik, Heather J.
出版 2019
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Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles
由
Duan, Chenru
,
Chen, Shuxin
,
Taylor, Michael G.
,
Liu, Fang
,
Kulik, Heather J.
出版 2021
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6
MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks
由
Nandy, Aditya
,
Terrones, Gianmarco
,
Arunachalam, Naveen
,
Duan, Chenru
,
Kastner, David W.
,
Kulik, Heather J.
出版 2022
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Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions
由
Taylor, Michael G.
,
Yang, Tzuhsiung
,
Lin, Sean
,
Nandy, Aditya
,
Janet, Jon Paul
,
Duan, Chenru
,
Kulik, Heather J.
出版 2020
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