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Rated NaN/5 by NaN customersNaNLearning Based Forward Modeling and Inversion Techniques for Computational Physics
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Rated NaN/5 by NaN customers()Learning Based Forward Modeling and Inversion Techniques for Computational Physics
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This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.
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This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.
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Listed on 12 June, 2024
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Rated NaN/5 by NaN customersNaNLearning Based Forward Modeling and Inversion Techniques for Computational Physics
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Rated NaN/5 by NaN customers()Learning Based Forward Modeling and Inversion Techniques for Computational Physics
0review
$5.00
Rated NaN/5 by NaN customersNaN
people viewing this product right now.
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INSTANT DOWNLOAD
people viewing this product right now.
Payment Methods:
Delivery & Return Policy
Shipping and Return Policy
Returns:Accepted
Exceptions may apply
prodactpdf
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Item description from the seller
This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.
Item description from the seller
This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.
Rating & Reviews
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Listed on 12 June, 2024
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