• Contact

  • Newsletter

  • About us

  • Delivery options

  • Prospero Book Market Podcast

  • Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods

    Data-Based Methods for Materials Design and Discovery by Pilania, Ghanshyam; Balachandran, Prasanna V.; Gubernatis, James E.;

    Basic Ideas and General Methods

    Series: Synthesis Lectures on Materials and Optics;

      • GET 8% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 87.00
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        36 083 Ft (34 365 Ft + 5% VAT)
      • Discount 8% (cc. 2 887 Ft off)
      • Discounted price 33 197 Ft (31 616 Ft + 5% VAT)

    36 083 Ft

    Availability

    Uncertain availability. Please turn to our customer service.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Morgan & Claypool Publishers
    • Date of Publication 30 March 2020
    • Number of Volumes Paperback

    • ISBN 9781681737379
    • Binding Paperback
    • No. of pages188 pages
    • Size 235x191 mm
    • Language English
    • 0

    Categories

    Short description:

    Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions.

    More

    Long description:

    Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.

    More