תמונות העטיפה

Machine Learning in Molecular Sciences

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 sc...

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שמור ב:
מידע ביבליוגרפי
מחבר תאגידי: SpringerLink (Online service)
מחברים אחרים: Qu, Chen (Editor), Liu, Hanchao (Editor)
פורמט: אלקטרוני ספר אלקטרוני
שפה:אנגלית
יצא לאור: Cham : Springer International Publishing : Imprint: Springer, 2023.
מהדורה:1st ed. 2023.
סדרה:Challenges and Advances in Computational Chemistry and Physics, 36
נושאים:
Machine learning.
Artificial intelligence.
Molecules > Models.
Chemistry, Physical and theoretical.
Chemistry > Data processing.
Bioinformatics.
Machine Learning.
Artificial Intelligence.
Molecular Modelling.
Theoretical Chemistry.
Computational Chemistry.
Computational and Systems Biology.
גישה מקוונת:https://doi.org/10.1007/978-3-031-37196-7
תגים: הוספת תג
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תוכן הענינים:
  • An Introduction to Machine Learning in Molecular Sciences
  • Graph Neural Networks for Molecules
  • Voxelized representations of atomic systems for machine learning applications
  • Development of exchange-correlation functionals assisted by machine learning
  • Machine-Learning for Static and Dynamic Electronic Structure Theory
  • Data Quality, Data Sampling and Data Fitting: A Tutorial Guide for Constructing Full-dimensional Accurate Potential Energy Surfaces (PESs) of Molecules and Reactions
  • Machine Learning Applications in Chemical Kinetics and Thermochemistry
  • Synthesize in A Smart Way: A Brief Introduction to Intelligence and Automation in Organic Synthesis
  • Machine Learning for Protein Engineering.

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