Titlebook: Deep Learning and Computational Physics; Deep Ray,Orazio Pinti,Assad A. Oberai Textbook 2024 The Editor(s) (if applicable) and The Author(

HAVEN

书目名称Deep Learning and Computational Physics影响因子(影响力)




书目名称Deep Learning and Computational Physics影响因子(影响力)学科排名




书目名称Deep Learning and Computational Physics网络公开度




书目名称Deep Learning and Computational Physics网络公开度学科排名




书目名称Deep Learning and Computational Physics被引频次




书目名称Deep Learning and Computational Physics被引频次学科排名




书目名称Deep Learning and Computational Physics年度引用




书目名称Deep Learning and Computational Physics年度引用学科排名




书目名称Deep Learning and Computational Physics读者反馈




书目名称Deep Learning and Computational Physics读者反馈学科排名

粗俗人

Glucocorticoids

Textbook 2024y set of tools. It is intended for senior undergraduate and graduate students in science and engineering programs. It is used as a textbook for a course (or a course sequence) for senior-level undergraduate or graduate-level students. .

employor

https://doi.org/10.1007/978-3-030-23541-3tion and natural language processing. But the last few years have also witnessed the emergence of machine learning (in particular deep learning) algorithms to solve physics-driven problems, such as approximating solutions to partial differential equations and inverse problems.

eulogize

Introduction,tion and natural language processing. But the last few years have also witnessed the emergence of machine learning (in particular deep learning) algorithms to solve physics-driven problems, such as approximating solutions to partial differential equations and inverse problems.

生来

Textbook 2024s strong connections between deep learning algorithms and the techniques of computational physics to achieve two important goals. First, it uses concepts from computational physics to develop an understanding of deep learning algorithms. Second, it describes several novel deep learning algorithms fo

生来

Comprise

Siddhartha Asthana,Pushpendra Singhly used methods include finite difference/volume methods, finite element methods, spectral Galerkin methods, and also deep neural networks! To better appreciate some of these methods, especially deep neural networks, let us consider a simple model problem describing the scalar advection-diffusion problem in one-dimension.

Hirsutism

MORPH

nterested in modeling physical phenomena with a complementary set of tools. It is intended for senior undergraduate and graduate students in science and engineering programs. It is used as a textbook for a course (or a course sequence) for senior-level undergraduate or graduate-level students. .978-3-031-59347-5978-3-031-59345-1