日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Human interpretable structure-property relationships in chemistry using explainable machine learning and large language models

利用可解释机器学习和大型语言模型,构建化学中人类可理解的结构-性质关系

Wellawatte, Geemi P; Schwaller, Philippe

Assessment of chemistry knowledge in large language models that generate code

评估生成代码的大型语言模型中的化学知识

White, Andrew D; Hocky, Glen M; Gandhi, Heta A; Ansari, Mehrad; Cox, Sam; Wellawatte, Geemi P; Sasmal, Subarna; Yang, Ziyue; Liu, Kangxin; Singh, Yuvraj; Peña Ccoa, Willmor J

A Perspective on Explanations of Molecular Prediction Models

分子预测模型解释的视角

Wellawatte, Geemi P; Gandhi, Heta A; Seshadri, Aditi; White, Andrew D

Neural potentials of proteins extrapolate beyond training data

蛋白质的神经潜能可以推断出训练数据之外的情况

Wellawatte, Geemi P; Hocky, Glen M; White, Andrew D

Model agnostic generation of counterfactual explanations for molecules

模型无关的分子反事实解释生成

Wellawatte, Geemi P; Seshadri, Aditi; White, Andrew D

Correction: Graph neural network based coarse-grained mapping prediction

更正:基于图神经网络的粗粒度映射预测

Li, Zhiheng; Wellawatte, Geemi P; Chakraborty, Maghesree; Gandhi, Heta A; Xu, Chenliang; White, Andrew D

Graph neural network based coarse-grained mapping prediction

基于图神经网络的粗粒度映射预测

Li, Zhiheng; Wellawatte, Geemi P; Chakraborty, Maghesree; Gandhi, Heta A; Xu, Chenliang; White, Andrew D