快速预测全旋转系统使用不确定性意识机器学习.
1Department of Computer Science, University of Chicago Chicago USA williamsjl@uchicago.edu ericj@uchicago.edu.
Chemical science
|October 13, 2023
概括
这项研究介绍了不确定性全旋系统预测 (FullSSPrUCe),这是一种用于准确核磁共振 (NMR) 光谱模拟的机器学习方法. FullSSPrUCe增强了化学转移和标量合的预测,提高了准确性和量化预测的信心.
科学领域:
- 计算化学的计算化学
- 机器学习 机器学习
- 频谱学是一种光谱学.
背景情况:
- 精确模拟溶液核磁共振 (NMR) 光谱对于分子结构的确定至关重要.
- 传统方法依赖于启发式技术或初始计算化学,这可能是计算密集型或缺乏全面的预测能力.
研究的目的:
- 开发一种新的机器学习技术,用于准确预测NMR光谱中的化学转移和标量合参数.
- 为强大的光谱模拟引入一种不确定性意识的深度学习方法.
- 改进现有的最先进的方法来预测NMR光谱参数.
主要方法:
- 一种新的机器学习技术,将不确定性意识深度学习与快速形状几何估计相结合.
- 完全旋转系统预测与不确定性 (FullSSPrUCe) 模型的发展.
- 使用分歧规范化来增加实验数据与初始数据.
主要成果:
- 在预测化学转移值方面取得了很高的准确性:质子在0.209 ppm内,碳在1.213 ppm内.
- 成功预测了所有标量合值,包括3JHH,准确度在0.838 Hz和1.392 Hz之间.
- 在不确定性量化和预测准确性之间显示出强烈的相关性,顶级预测显示出明显减少的误差.
结论:
- 全SSPrUCe方法在NMR光谱模拟的准确性和可靠性方面取得了显著的进步.
- 不确定性量化提供了一个有价值的预测信心指标,对于实验数据解释至关重要.
- 该方法有效地处理立体异构,并集成多种数据源,以提高模型性能.
相关概念视频
00:59Uncertainty: Overview
570
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
570
01:10Propagation of Uncertainty from Systematic Error
534
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
534
00:59Propagation of Uncertainty from Random Error
704
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
704
01:03Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
00:54Uncertainty: Confidence Intervals
4.1K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
4.1K
02:24Predicting Reaction Outcomes
8.5K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.5K