Description: Probabilistic Numerics by Philipp Hennig, Michael A. Osborne, Hans P. Kersting Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This text provides a first comprehensive introduction to probabilistic numerics, aimed at Masters and PhD students, as well as postgraduate researchers in artificial intelligence, computer science, statistics, and applied mathematics. It contains extensive background material, and uses figures, exercises, and worked examples to develop intuition. Publisher Description Probabilistic numerical computation formalises the connection between machine learning and applied mathematics. Numerical algorithms approximate intractable quantities from computable ones. They estimate integrals from evaluations of the integrand, or the path of a dynamical system described by differential equations from evaluations of the vector field. In other words, they infer a latent quantity from data. This book shows that it is thus formally possible to think of computational routines as learning machines, and to use the notion of Bayesian inference to build more flexible, efficient, or customised algorithms for computation. The text caters for Masters and PhD students, as well as postgraduate researchers in artificial intelligence, computer science, statistics, and applied mathematics. Extensive background material is provided along with a wealth of figures, worked examples, and exercises (with solutions) to develop intuition. Author Biography Philipp Hennig holds the Chair for the Methods of Machine Learning at the University of TÜbingen, and an adjunct position at the Max Planck Institute for Intelligent Systems. He has dedicated most of his career to the development of Probabilistic Numerical Methods. Hennigs research has been supported by Emmy Noether, Max Planck and ERC fellowships. He is a co-Director of the Research Program for the Theory, Algorithms and Computations of Learning Machines at the European Laboratory for Learning and Intelligent Systems (ELLIS). Michael A. Osborne is Professor of Machine Learning at the University of Oxford, and a co-Founder of Mind Foundry Ltd. His research has attracted £10.6M of research funding and has been cited over 15,000 times. He is very, very Bayesian. Hans P. Kersting is a postdoctoral researcher at INRIA and École Normale Supérieure in Paris, working in machine learning with expertise in Bayesian inference, dynamical systems, and optimisation. Details ISBN 1107163447 ISBN-13 9781107163447 Title Probabilistic Numerics Author Philipp Hennig, Michael A. Osborne, Hans P. Kersting Format Hardcover Year 2022 Pages 410 Publisher Cambridge University Press GE_Item_ID:158390768; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 81.41 USD
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End Time: 2024-09-28T06:44:02.000Z
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ISBN-13: 9781107163447
Book Title: Probabilistic Numerics
Number of Pages: 300 Pages
Language: English
Publication Name: Probabilistic Numerics : Computation As Machine Learning
Publisher: Cambridge University Press
Publication Year: 2022
Subject: General
Item Height: 0.9 in
Type: Textbook
Subject Area: Computers, Science
Author: Philipp Hennig, Hans P. Kersting, Michael A. Osborne
Item Length: 10.2 in
Item Width: 8.2 in
Format: Hardcover
