Machine Learning in Molecular Sciences
Qu, Chen, Liu, Hanchao
- 出版商: Springer
- 出版日期: 2023-10-02
- 售價: $7,750
- 貴賓價: 9.5 折 $7,363
- 語言: 英文
- 頁數: 317
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 303137195X
- ISBN-13: 9783031371950
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相關分類:
Machine Learning
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相關主題
商品描述
Machine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sciences. Written by an international group of renowned experts, this edited volume covers both the machine learning methodologies and state-of-the-art machine learning applications in a wide range of topics in molecular sciences, from electronic structure theory to nuclear dynamics of small molecules, to the design and synthesis of large organic and biological molecules. This book is a valuable resource for researchers and students interested in applying machine learning in the research of molecular sciences.
商品描述(中文翻譯)
機器學習和人工智慧的快速進展在計算硬體、演算法和資料累積方面推動了分子科學各個領域的研究。本書介紹了機器學習在分子科學廣泛研究領域中的最新應用。由國際知名專家組成的編輯團隊撰寫,本書涵蓋了機器學習方法論和分子科學各個主題的最新應用,包括從電子結構理論到小分子的核動力學,以及大型有機和生物分子的設計和合成。本書對於有興趣在分子科學研究中應用機器學習的研究人員和學生來說是一個寶貴的資源。
作者簡介
Chen Qu is currently a research associate of National Institute of Standards and Technology. His current research focuses on applying machine learning methods to predict important chemical properties such as gas chromatography retention indices and mass spectra. He received his Ph.D. at Emory University, where he conducted research primarily on machine learning potential energy surfaces, under the guidance of Prof. Joel Bowman. Hanchao Liu is currently a machine learning engineer at Google. His work focuses on building large-scale machine learning infrastructures and platforms. Dr. Liu received his Ph.D. in computational chemistry at Emory University under the tutelage of Prof. Joel Bowman, where he applied computational and machine learning methods to study the vibrational dynamics and spectra of various forms of water.
作者簡介(中文翻譯)
陳曲目前是美國國家標準與技術研究所的研究助理。他目前的研究專注於應用機器學習方法來預測重要的化學性質,例如氣相色譜保留指數和質譜。他在Emory大學獲得了博士學位,他在那裡主要在機器學習潛在能量表面方面進行研究,並在Joel Bowman教授的指導下進行研究。
韓超目前是Google的機器學習工程師。他的工作重點是建立大規模的機器學習基礎設施和平台。韓博士在Emory大學獲得了計算化學的博士學位,他在Joel Bowman教授的指導下,應用計算和機器學習方法研究了不同形式的水的振動動力學和光譜。