| bibtype |
J -
Journal Article
|
| ARLID |
0542523 |
| utime |
20240103225818.9 |
| mtime |
20210520235959.9 |
| WOS |
000632795500001 |
| SCOPUS |
85103167709 |
| DOI |
10.1080/03081079.2021.1895142 |
| title
(primary) (eng) |
Foundations of compositional models: inference |
| specification |
| page_count |
24 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0256794 |
| ISSN |
0308-1079 |
| title
|
International Journal of General Systems |
| volume_id |
50 |
| volume |
4 (2021) |
| page_num |
409-433 |
| publisher |
|
|
| keyword |
Probability distribution |
| keyword |
multidimensionality |
| keyword |
marginalization |
| keyword |
conditioning |
| keyword |
causality |
| keyword |
intervention |
| author
(primary) |
| ARLID |
cav_un_auth*0101118 |
| name1 |
Jiroušek |
| name2 |
Radim |
| institution |
UTIA-B |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept (eng) |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department (eng) |
MTR |
| full_dept |
Department of Decision Making Theory |
| share |
50 |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0216188 |
| name1 |
Kratochvíl |
| name2 |
Václav |
| institution |
UTIA-B |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| full_dept |
Department of Decision Making Theory |
| country |
CZ |
| share |
50 |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0393863 |
| name1 |
Bína |
| name2 |
Vladislav |
| institution |
UTIA-B |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GA19-06569S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0380559 |
|
| abstract
(eng) |
Compositional models, as an alternative to Bayesian networks, are assembled from a system of low-dimensional distributions. Thus, the respective apparatus falls fully into probability theory. The present paper surveys the results supporting the design of computational procedures, without which the application of these models to practical problems would be impossible. The methods of inference cannot do without a possibility to focus on a part of the considered multidimensional model and to incorporate data describing the actual situation. Thus, the paper shows how to compute marginals and conditionals of multidimensional models. Also, the paper briefly solves the problem of computing the effect of an intervention, in case the model is interpreted as a causal model. |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2022 |
| num_of_auth |
2 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0320293 |
| confidential |
S |
| mrcbC86 |
3+4 Article Computer Science Theory Methods|Ergonomics |
| mrcbC91 |
C |
| mrcbT16-e |
COMPUTERSCIENCETHEORYMETHODS |
| mrcbT16-j |
0.417 |
| mrcbT16-s |
0.720 |
| mrcbT16-D |
Q3 |
| mrcbT16-E |
Q3 |
| arlyear |
2021 |
| mrcbU14 |
85103167709 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000632795500001 WOS |
| mrcbU63 |
cav_un_epca*0256794 International Journal of General Systems 0308-1079 1563-5104 Roč. 50 č. 4 2021 409 433 Taylor & Francis |
|