Machine Learning in Molecular Sciences
Qu, Chen, Liu, Hanchao
- 出版商: Springer
- 出版日期: 2024-10-03
- 售價: $7,050
- 貴賓價: 9.5 折 $6,698
- 語言: 英文
- 頁數: 317
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3031371984
- ISBN-13: 9783031371981
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相關分類:
Machine Learning
海外代購書籍(需單獨結帳)
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，促進了各種分子科學領域的研究，這得益於計算硬體、演算法和數據積累的迅速發展。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。這本編輯書籍由一群國際知名專家撰寫，涵蓋了機器學習的方法論以及在分子科學各個主題中的最先進機器學習應用，從電子結構理論到小分子的核動力學，再到大型有機和生物分子的設計與合成。本書是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，極具價值的資源。
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。他在埃默里大學獲得博士學位，主要在喬爾·鮑曼教授的指導下進行機器學習潛能能量面方面的研究。
劉漢超目前是谷歌的機器學習工程師。他的工作專注於構建大規模的機器學習基礎設施和平台。劉博士在埃默里大學獲得計算化學博士學位，並在喬爾·鮑曼教授的指導下，應用計算和機器學習方法研究各種形式水的振動動力學和光譜。
