April 2024

ExploTec / 2024 / April
April 19, 2024 In Unkategorisiert By

Extrapolation Validation (EV): A Common Validation Way for Mitigating System Finding out Extrapolation Chance

Digital Discovery, 2024, Accepted ManuscriptDOI: 10.1039/D3DD00256J, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. Mengxian Yu, Yin-Ning Zhou, Qiang Wang, Fangyou YanMachine Learning (ML) can provide decision-making advice for major challenges in science and engineering, and its

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deepspinn-–-deep-reinforcement-finding-out-for-molecular-construction-prediction-from-infrared-and-13c-nmr-spectra
April 19, 2024 In Unkategorisiert By Sriram Devata

DeepSPInN – deep reinforcement finding out for molecular construction prediction from infrared and 13C NMR spectra

Digital Discovery, 2024, 3,818-829DOI: 10.1039/D4DD00008K, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Sriram Devata, Bhuvanesh Sridharan, Sarvesh Mehta, Yashaswi Pathak, Siddhartha Laghuvarapu, Girish Varma, U. Deva PriyakumarDeepSPInI is a deep reinforcement learning method that predicts the molecular

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benchmarking-machine-readable-vectors-of-chemical-reactions-on-computed-activation-limitations
April 19, 2024 In Unkategorisiert By Puck van Gerwen

Benchmarking machine-readable vectors of chemical reactions on computed activation limitations

Digital Discovery, 2024, Advance ArticleDOI: 10.1039/D3DD00175J, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Puck van Gerwen, Ksenia R. Briling, Yannick Calvino Alonso, Malte Franke, Clemence CorminboeufWe benchmark various methods for the prediction of computed activation barriers on

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evaluating-device-gear-for-optical-chemical-construction-popularity
April 19, 2024 In Unkategorisiert By Aleksei Krasnov

Evaluating device gear for optical chemical construction popularity

Digital Discovery, 2024, 3,681-693DOI: 10.1039/D3DD00228D, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Aleksei Krasnov, Shadrack J. Barnabas, Timo Boehme, Stephen K. Boyer, Lutz WeberThe extraction of chemical information from images, also known as Optical Chemical Structure Recognition

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egraffbench:-analysis-of-equivariant-graph-neural-community-power-fields-for-atomistic-simulations
April 19, 2024 In Unkategorisiert By Vaibhav Bihani

EGraFFBench: analysis of equivariant graph neural community power fields for atomistic simulations

Digital Discovery, 2024, 3,759-768DOI: 10.1039/D4DD00027G, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Vaibhav Bihani, Sajid Mannan, Utkarsh Pratiush, Tao Du, Zhimin Chen, Santiago Miret, Matthieu Micoulaut, Morten M. Smedskjaer, Sayan Ranu, N. M. Anoop KrishnanEGraFFBench: a framework

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studying-conditional-insurance-policies-for-crystal-design-the-use-of-offline-reinforcement-studying
April 19, 2024 In Unkategorisiert By Prashant Govindarajan

Studying conditional insurance policies for crystal design the use of offline reinforcement studying

Digital Discovery, 2024, 3,769-785DOI: 10.1039/D4DD00024B, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath ChandarConservative Q-learning for band-gap conditioned crystal design with DFT evaluations – the model is

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