首页|Peking University Reports Findings in Machine Learning (Exploring Chemical React ion Space with Machine Learning Models: Representation and Feature Perspective)
Peking University Reports Findings in Machine Learning (Exploring Chemical React ion Space with Machine Learning Models: Representation and Feature Perspective)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Beijing,Peo ple's Republic of China,by NewsRx correspondents,research stated,"Chemical re actions serve as foundational building blocks for organic chemistry and drug des ign. In the era of large AI models,data-driven approaches have emerged to innov ate the design of novel reactions,optimize existing ones for higher yields,and discover new pathways for synthesizing chemical structures comprehensively." Our news editors obtained a quote from the research from Peking University,"To effectively address these challenges with machine learning models,it is imperat ive to derive robust and informative representations or engage in feature engine ering using extensive data sets of reactions. This work aims to provide a compre hensive review of established reaction featurization approaches,offering insigh ts into the selection of representations and the design of features for a wide a rray of tasks. The advantages and limitations of employing SMILES,molecular fin gerprints,molecular graphs,and physics-based properties are meticulously elabo rated. Solutions to bridge the gap between different representations will also b e critically evaluated." According to the news editors,the research concluded: "Additionally,we introdu ce a new frontier in chemical reaction pretraining,holding promise as an innova tive yet unexplored avenue."
BeijingPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine Learning
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