Geometry of deep learning: a signal processing perspective
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Singapore
Springer
[2022]
|
| Ausgabe: | 1st ed. 2022 |
| Schriftenreihe: | Mathematics in industry
volume 37 |
| Schlagworte: | |
| Beschreibung: | Literaturverzeichnis Seite 317-325 |
| Beschreibung: | xvi, 330 Seiten Illustrationen |
| ISBN: | 9789811660481 |
| ISSN: | 2198-3283 |
Internformat
MARC
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| 500 | |a Literaturverzeichnis Seite 317-325 | ||
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| 650 | 4 | |a Artificial Intelligence | |
| 650 | 4 | |a Mathematical Models of Cognitive Processes and Neural Networks | |
| 650 | 4 | |a Mathematical and Computational Biology | |
| 650 | 4 | |a Functional analysis | |
| 650 | 4 | |a Geometry, Differential | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 650 | 4 | |a Biomathematics | |
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Datensatz im Suchindex
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| author | Ye, Jong Chul ca. 21. Jh |
| author_GND | (DE-588)1259447170 |
| author_facet | Ye, Jong Chul ca. 21. Jh |
| author_role | aut |
| author_sort | Ye, Jong Chul ca. 21. Jh |
| author_variant | j c y jc jcy |
| building | Verbundindex |
| bvnumber | BV049607875 |
| classification_rvk | ST 300 |
| classification_tum | MAT 000 |
| ctrlnum | (OCoLC)1405904633 (DE-599)BVBBV049607875 |
| dewey-full | 515.7 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 515 - Analysis |
| dewey-raw | 515.7 |
| dewey-search | 515.7 |
| dewey-sort | 3515.7 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
| discipline_str_mv | Mathematik |
| edition | 1st ed. 2022 |
| format | Book |
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| id | DE-604.BV049607875 |
| illustrated | Illustrated |
| index_date | 2024-07-03T23:35:46Z |
| indexdate | 2024-07-20T06:25:12Z |
| institution | BVB |
| isbn | 9789811660481 |
| issn | 2198-3283 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034952149 |
| oclc_num | 1405904633 |
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| owner_facet | DE-522 DE-573 |
| physical | xvi, 330 Seiten Illustrationen |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| record_format | marc |
| series | Mathematics in industry |
| series2 | Mathematics in industry |
| spelling | Ye, Jong Chul ca. 21. Jh. Verfasser (DE-588)1259447170 aut Geometry of deep learning a signal processing perspective by Jong Chul Ye Singapore Springer [2022] xvi, 330 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Mathematics in industry volume 37 Literaturverzeichnis Seite 317-325 Differential Geometry Artificial Intelligence Mathematical Models of Cognitive Processes and Neural Networks Mathematical and Computational Biology Functional analysis Geometry, Differential Artificial intelligence Neural networks (Computer science) Biomathematics Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Deep learning (DE-588)1135597375 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s Künstliche Intelligenz (DE-588)4033447-8 s Deep learning (DE-588)1135597375 s DE-604 Erscheint auch als Online-Ausgabe 978-981-16-6046-7 Mathematics in industry volume 37 (DE-604)BV014253721 37 |
| spellingShingle | Ye, Jong Chul ca. 21. Jh Geometry of deep learning a signal processing perspective Differential Geometry Artificial Intelligence Mathematical Models of Cognitive Processes and Neural Networks Mathematical and Computational Biology Functional analysis Geometry, Differential Artificial intelligence Neural networks (Computer science) Biomathematics Künstliche Intelligenz (DE-588)4033447-8 gnd Neuronales Netz (DE-588)4226127-2 gnd Deep learning (DE-588)1135597375 gnd Mathematics in industry |
| subject_GND | (DE-588)4033447-8 (DE-588)4226127-2 (DE-588)1135597375 |
| title | Geometry of deep learning a signal processing perspective |
| title_auth | Geometry of deep learning a signal processing perspective |
| title_exact_search | Geometry of deep learning a signal processing perspective |
| title_exact_search_txtP | Geometry of Deep Learning A Signal Processing Perspective |
| title_full | Geometry of deep learning a signal processing perspective by Jong Chul Ye |
| title_fullStr | Geometry of deep learning a signal processing perspective by Jong Chul Ye |
| title_full_unstemmed | Geometry of deep learning a signal processing perspective by Jong Chul Ye |
| title_short | Geometry of deep learning |
| title_sort | geometry of deep learning a signal processing perspective |
| title_sub | a signal processing perspective |
| topic | Differential Geometry Artificial Intelligence Mathematical Models of Cognitive Processes and Neural Networks Mathematical and Computational Biology Functional analysis Geometry, Differential Artificial intelligence Neural networks (Computer science) Biomathematics Künstliche Intelligenz (DE-588)4033447-8 gnd Neuronales Netz (DE-588)4226127-2 gnd Deep learning (DE-588)1135597375 gnd |
| topic_facet | Differential Geometry Artificial Intelligence Mathematical Models of Cognitive Processes and Neural Networks Mathematical and Computational Biology Functional analysis Geometry, Differential Artificial intelligence Neural networks (Computer science) Biomathematics Künstliche Intelligenz Neuronales Netz Deep learning |
| volume_link | (DE-604)BV014253721 |
| work_keys_str_mv | AT yejongchul geometryofdeeplearningasignalprocessingperspective |