Machine learning in pure mathematics and theoretical physics / (Record no. 49727)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03422nam a2200409 a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | WSP |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260416153408.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 230114s2023 enk ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781800613706 |
| -- | (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1800613709 |
| -- | (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Cancelled/invalid ISBN | 9781800613690 |
| -- | (hbk.) |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM |
| Subject category code subdivision | 094000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MAT |
| Subject category code subdivision | 000000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | SCI |
| Subject category code subdivision | 055000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3/1015 |
| Edition number | 23 |
| 049 ## - LOCAL HOLDINGS (OCLC) | |
| Holding library | MAIN |
| 245 00 - TITLE STATEMENT | |
| Title | Machine learning in pure mathematics and theoretical physics / |
| Statement of responsibility, etc | edited by Yang-Hui He. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | London : |
| Name of publisher, distributor, etc | World Scientific Publishing Europe Ltd., |
| Date of publication, distribution, etc | c2023. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource (xxii, 395 p.) |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Contents | Machine learning meets number theory : the data science of Birch-Swinnerton-Dyer -- On the dynamics of inference and learning -- Machine learning : the dimension of a polytope -- Intelligent explorations of the string theory landscape -- Deep learning : complete intersection Calabi-Yau manifolds -- Deep-learning the landscape -- hep-th -- Symmetry-via-duality : invariant neural network densities from parameter-space correlators -- Supervised learning of arithmetic invariants -- Calabi-Yau volumes, reflexive polytopes and machine learning. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "The juxtaposition of "machine learning" and "pure mathematics and theoretical physics" may first appear as contradictory in terms. The rigours of proofs and derivations in the latter seem to reside in a different world from the randomness of data and statistics in the former. Yet, an often under-appreciated component of mathematical discovery, typically not presented in a final draft, is experimentation: both with ideas and with mathematical data. Think of the teenage Gauss, who conjectured the Prime Number Theorem by plotting the prime-counting function, many decades before complex analysis was formalized to offer a proof. Can modern technology in part mimic Gauss's intuition? The past five years saw an explosion of activity in using AI to assist the human mind in uncovering new mathematics: finding patterns, accelerating computations, and raising conjectures via the machine learning of pure, noiseless data. The aim of this book, a first of its kind, is to collect research and survey articles from experts in this emerging dialogue between theoretical mathematics and machine learning. It does not dwell on the well-known multitude of mathematical techniques in deep learning, but focuses on the reverse relationship: how machine learning helps with mathematics. Taking a panoramic approach, the topics range from combinatorics to number theory, and from geometry to quantum field theory and string theory. Aimed at PhD students as well as seasoned researchers, each self-contained chapter offers a glimpse of an exciting future of this symbiosis"-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematics |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Physics |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | He, Yang-Hui, |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://www.worldscientific.com/worldscibooks/10.1142/q0404#t=toc">https://www.worldscientific.com/worldscibooks/10.1142/q0404#t=toc</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Electronic Books |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. | |
| -- | Publisher's website. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | Mode of access: World Wide Web. |
| 538 ## - SYSTEM DETAILS NOTE | |
| System details note | System requirements: Adobe Acrobat Reader. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| General subdivision | Data processing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| General subdivision | Data processing. |
| 655 #0 - INDEX TERM--GENRE/FORM | |
| Genre/form data or focus term | Electronic books. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Dates associated with a name | 1975- |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Location | Date of Cataloging | Total Checkouts | Full call number | Barcode | Date last seen | Uniform Resource Identifier | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | CUTN Central Library | CUTN Central Library | 16/04/2026 | 006.3/1015 | EB04973 | 16/04/2026 | https://doi.org/10.1142/q0404 | 16/04/2026 | Electronic Books |