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{
"item_title" : "Bayesian Optimization for Materials Science",
"item_author" : [" Daniel Packwood "],
"item_description" : "Is a timely publication as Bayesian optimization gains interest in materials science, and is one of the few introductions to this method for materials scientistsMakes the mathematical content appealing to materials scientists with its interesting application to structure optimization problemsEnables materials scientists to use Bayesian optimization in their own research",
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Bayesian Optimization for Materials Science
Overview
Is a timely publication as Bayesian optimization gains interest in materials science, and is one of the few introductions to this method for materials scientists
Makes the mathematical content appealing to materials scientists with its interesting application to structure optimization problems
Enables materials scientists to use Bayesian optimization in their own research
This item is Non-Returnable
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Details
- ISBN-13: 9789811067808
- ISBN-10: 9811067805
- Publisher: Springer
- Publish Date: October 2017
- Dimensions: 9.21 x 6.14 x 0.11 inches
- Shipping Weight: 0.19 pounds
- Page Count: 42
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