000			02086nam a22004333i 4500
001			EBC3074890
003			MiAaPQ
005			20240729124459.0
006			m o d |
007			cr cnu||||||||
008			240724s1996 xx o ||||0 eng d
020			_a9781461207450 _q(electronic bk.)
020			_z9780387947242
035			_a(MiAaPQ)EBC3074890
035			_a(Au-PeEL)EBL3074890
035			_a(CaPaEBR)ebr10918311
035			_a(OCoLC)958525906
040			_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ
050		4	_aQA273.A1-274.9
100	1		_aNeal, Radford M.
245	1	0	_aBayesian Learning for Neural Networks.
250			_a1st ed.
264		1	_aNew York, NY : _bSpringer, _c1996.
264		4	_c©1996.
300			_a1 online resource (194 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aLecture Notes in Statistics Series ; _vv.118
505	0		_aLecture Notes in Statistics -- Bayesian Learning for Neural Networks -- Copyright -- Preface -- Contents -- List of Figures -- Chapter 1 Introduction -- Chapter 2 Priors for Infinite Networks -- Chapter 3 Monte Carlo Implementation -- Chapter 4 Evaluation of Neural Network Models -- Chapter 5 Conclusions and Further Work -- Appendix A Details of the Implementation -- Appendix B Obtaining the software -- Bibliography -- Index.
588			_aDescription based on publisher supplied metadata and other sources.
590			_aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650		0	_aBayesian statistical decision theory.
655		4	_aElectronic books.
776	0	8	_iPrint version: _aNeal, Radford M. _tBayesian Learning for Neural Networks _dNew York, NY : Springer,c1996 _z9780387947242
797	2		_aProQuest (Firm)
830		0	_aLecture Notes in Statistics Series
856	4	0	_uhttps://ebookcentral.proquest.com/lib/orpp/detail.action?docID=3074890 _zClick to View
999			_c67378 _d67378