Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
1
views
0
references
Top references
cited by
4
Cite as...
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
2,628
similar
All similar
Record
: found
Abstract
: not found
Book
: not found
Innovations in Bayesian Networks
other
Editor(s):
Dawn E. Holmes
,
Lakhmi C. Jain
Publication date
(Print):
2008
Publisher:
Springer Berlin Heidelberg
Read this book at
Publisher
Buy book
Review
Review book
Invite someone to review
Bookmark
Cite as...
There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Cardiovascular Innovations and Applications
Author and book information
Book
ISBN (Print):
978-3-540-85065-6
ISBN (Electronic):
978-3-540-85066-3
Publication date (Print):
2008
DOI:
10.1007/978-3-540-85066-3
SO-VID:
d19f634f-65f8-4d90-89e7-5ec82fc24ff4
History
Data availability:
Comments
Comment on this book
Sign in to comment
Book chapters
pp. 33
A Tutorial on Learning with Bayesian Networks
Similar content
2,628
AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics.
Authors:
Johan Nylander
,
James C Wilgenbusch
,
Dan L Warren
…
Bayesian multi-model projections of extreme hydroclimatic events under RCPs scenarios
Authors:
Jun ke Xia
,
Qiao-Hong Sun
,
Qing-Yun Duan
…
Reconstruction of a windborne insect invasion using a particle dispersal model, historical wind data, and Bayesian analysis of genetic data
Authors:
Tonya A Lander
,
Etienne Klein
,
Sylvie Oddou-Muratorio
…
See all similar
Cited by
4
Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm
Authors:
Jitian Xiao
,
Hongye Zhong
Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease
Authors:
Jose L. Cadavid
,
Nancy T. Li
,
Alison P. McGuigan
Quantifying (Hyper) Parameter Leakage in Machine Learning
Authors:
Vasisht Duddu
,
D Vijay Rao
See all cited by