Correction: Predicting small molecules solubility on endpoint devices using deep ensemble neural networks

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY Digital discovery Pub Date : 2024-05-03 DOI:10.1039/D4DD90020K

Mayk Caldas Ramos and Andrew D. White

引用次数: 0

Abstract

Correction for ‘Predicting small molecules solubility on endpoint devices using deep ensemble neural networks’ by Mayk Caldas Ramos and Andrew D. White, Digital Discovery, 2024, 3, 786–795, https://doi.org/10.1039/D3DD00217A.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

更正：利用深度集合神经网络预测小分子在终端设备上的溶解度

对 Mayk Caldas Ramos 和 Andrew D. White 的 "使用深度集合神经网络预测小分子在终端设备上的溶解度 "的更正，《数字发现》，2024 年 3 期，786-795，https://doi.org/10.1039/D3DD00217A。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Digital discovery

CiteScore

2.80

自引率

0.00%

发文量

期刊最新文献

Back cover ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials. Sorting polyolefins with near-infrared spectroscopy: identification of optimal data analysis pipelines and machine learning classifiers†‡ High accuracy uncertainty-aware interatomic force modeling with equivariant Bayesian neural networks† Correction: A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing