这本书《Machine Learning: A Physicist Perspective》由Nelson Bolivar撰写,主要从物理学家的角度探讨了机器学习的原理和应用。这本书旨在为包括物理学家、机器学习专家、学生和教授在内的广大读者提供一个全面的机器学习基础介绍,同时也为研究人员提供了深入理解机器学习原理的高级理论视角。 ### 第1章:机器学习基础...
Tom PurdieMedical Physicist, Princess Margaret Cancer Centre, Canada INTERVIEW WITH FREDRIK LÖFMAN AT ASTRO 2019 Physics World met up with us and Fredrik Löfman, who is heading up our Machine learning department. Here is what he had to say. Please accept the use of cookies to see this...
For example, in the 2021 ML contest organized by the Society of Petrophysicist and Well Log Analysts (SPWLA) (Yu et al., 2021), all five teams predicted shear slowness (DTS) to be much higher than the log measurement in the fastest zone as highlighted in Fig. 2. Download: Download ...
Traditionally, an indispensable tool to the high energy physicist is the extensive tables of [1]. More contemporary usage, with the advent of computing power of the ordinary laptop, has relied on the likes of highly convenient software such as “LieART” [2]. Such computer algebra methods, ...
The Nobel Prize in physics was awarded a day after two American scientists won the medicine prize for their discovery of microRNA. The 2023 award went to French-Swedish physicist Anne L'Huillier, French scientist Pierre...
Physics, too, has fallen into the artificial intelligence hype with a clutch of researchers using machine learning to deal with complex problems regarding huge amount of data.
They even named their network in honor of Ludwig Boltzmann, the physicist whose work formed the foundation of statistical mechanics. And the connection between neural networks and physics isn’t a one-way street. Machine learning was crucial to the discovery of the Higgs boson, where it sorted ...
Diverse many-body systems, from soap bubbles to suspensions to polymers, learn and remember patterns in the drives that push them far from equilibrium. This learning may be leveraged for computation, memory, and engineering. Until now, many-body learning
2 Machine learning for theoretical physicists Since machine learning is not part of the everyday lexicon of a theoretical physicist, in this section we would like to review the basics of the subject, including all of the techniques that we utilized in this paper. The subject has a rich ...
Application of radiomics and machine learning in head and neck cancers. Int. J. Biol. Sci. 17, 475–486. https://doi.org/10.7150/ijbs.55716 (2021). Article PubMed PubMed Central Google Scholar Peeken, J. C. et al. Radiomics in radiooncology - challenging the medical physicist. Physic...