-
4
-
-
84896062859
-
Bayesian probabilities for constraint-based causal discovery
-
T. Claassen and T. Heskes. Bayesian probabilities for constraint-based causal discovery. In IJCAI-13, pages 2992-2996, 2013.
-
(2013)
IJCAI-13
, pp. 2992-2996
-
-
Claassen, T.1
Heskes, T.2
-
5
-
-
84888174793
-
Learning sparse causal models is not NP-hard
-
T. Claassen, J.M. Mooij, and T. Heskes. Learning Sparse Causal Models is not NP-hard. In UAI-13, pages 172-181, 2013.
-
(2013)
UAI-13
, pp. 172-181
-
-
Claassen, T.1
Mooij, J.M.2
Heskes, T.3
-
6
-
-
34249832377
-
A Bayesian method for the induction of probabilistic networks from data
-
G. F. Cooper and E. Herskovits. A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9: 309-347, 1992.
-
(1992)
Machine Learning
, vol.9
, pp. 309-347
-
-
Cooper, G.F.1
Herskovits, E.2
-
7
-
-
70450278796
-
Computing maximum likelihood estimates in recursive linear models with correlated errors
-
M. Drton, M. Eichler, and T. Richardson. Computing maximum likelihood estimates in recursive linear models with correlated errors. Journal of Machine Learning Research, 10: 2329-2348, 2009.
-
(2009)
Journal of Machine Learning Research
, vol.10
, pp. 2329-2348
-
-
Drton, M.1
Eichler, M.2
Richardson, T.3
-
8
-
-
80053152166
-
Maximum likelihood fitting of acyclic directed mixed graphs to binary data
-
R. Evans and T. Richardson. Maximum likelihood fitting of acyclic directed mixed graphs to binary data. In UAI-10, 2010.
-
(2010)
UAI-10
-
-
Evans, R.1
Richardson, T.2
-
9
-
-
84987892086
-
Graphs for margins of Bayesian networks
-
R.J. Evans. Graphs for margins of Bayesian networks. Scand. J. Stat., 43(3): 625-648, 2016.
-
(2016)
Scand. J. Stat.
, vol.43
, Issue.3
, pp. 625-648
-
-
Evans, R.J.1
-
11
-
-
84987994699
-
Markovian acyclic directed mixed graphs for discrete data
-
08
-
R.J. Evans and T.S. Richardson. Markovian acyclic directed mixed graphs for discrete data. Ann. Statist., 42(4): 1452-1482, 08 2014.
-
(2014)
Ann. Statist.
, vol.42
, Issue.4
, pp. 1452-1482
-
-
Evans, R.J.1
Richardson, T.S.2
-
13
-
-
84924033499
-
Clingo = ASP + control: Extended report
-
M. Gebser, R. Kaminski, B. Kaufmann, and T. Schaub. Clingo = ASP + control: Extended report. Technical report, University of Potsdam, 2014. http://www.cs.uni-potsdam.de/wv/pdfformat/gekakasc14a.pdf.
-
(2014)
Technical Report, University of Potsdam
-
-
Gebser, M.1
Kaminski, R.2
Kaufmann, B.3
Schaub, T.4
-
14
-
-
0000034390
-
Learning Gaussian networks
-
D. Geiger and D. Heckerman. Learning Gaussian networks. In UAI-94, pages 235-243, 1994.
-
(1994)
UAI-94
, pp. 235-243
-
-
Geiger, D.1
Heckerman, D.2
-
17
-
-
0012315692
-
A Bayesian approach to causal discovery
-
C. Glymour and G. F. Cooper, editors MIT Press
-
D. Heckerman, C. Meek, and G. Cooper. A Bayesian approach to causal discovery. In C. Glymour and G. F. Cooper, editors, Computation, Causation, and Discovery, pages 141-166. MIT Press, 1999.
-
(1999)
Computation, Causation, and Discovery
, pp. 141-166
-
-
Heckerman, D.1
Meek, C.2
Cooper, G.3
-
19
-
-
84923292776
-
Constraint-based causal discovery: Conflict resolution with answer set programming
-
A. Hyttinen, F. Eberhardt, and M. Järvisalo. Constraint-based causal discovery: Conflict resolution with answer set programming. In UAI-14, pages 340-349, 2014.
-
(2014)
UAI-14
, pp. 340-349
-
-
Hyttinen, A.1
Eberhardt, F.2
Järvisalo, M.3
-
22
-
-
0040086810
-
Strong completeness and faithfulness in Bayesian networks
-
C. Meek. Strong completeness and faithfulness in Bayesian networks. In UAI-95, pages 411-418, 1995.
-
(1995)
UAI-95
, pp. 411-418
-
-
Meek, C.1
-
24
-
-
84911533938
-
Fusion, propagation and structuring in belief networks
-
Technical Report 850022 (R-42)
-
J. Pearl. Fusion, propagation and structuring in belief networks. Technical Report 3, UCLA Computer Science Department, 1986. Technical Report 850022 (R-42).
-
(1986)
Technical Report 3, UCLA Computer Science Department
-
-
Pearl, J.1
-
27
-
-
0040630191
-
A discovery algorithm for directed cyclic graphs
-
T. Richardson. A discovery algorithm for directed cyclic graphs. In UAI-96, pages 454-461. 1996.
-
(1996)
UAI-96
, pp. 454-461
-
-
Richardson, T.1
-
28
-
-
0038107398
-
Markov properties for acyclic directed mixed graphs
-
T. Richardson. Markov properties for acyclic directed mixed graphs. Scand. J. Stat., 30(1): 145-157, 2003.
-
(2003)
Scand. J. Stat.
, vol.30
, Issue.1
, pp. 145-157
-
-
Richardson, T.1
-
29
-
-
0012720970
-
Automated discovery of linear feedback models
-
C. Glymour and G. F. Cooper, editors MIT Press
-
T. Richardson and P. Spirtes. Automated discovery of linear feedback models. In C. Glymour and G. F. Cooper, editors, Computation, Causation, and Discovery, pages 253-304. MIT Press, 1999.
-
(1999)
Computation, Causation, and Discovery
, pp. 253-304
-
-
Richardson, T.1
Spirtes, P.2
-
30
-
-
84965107424
-
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
-
D. Rothenhäusler, C. Heinze, J. Peters, and N. Meinshausen. BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions. In NIPS-15, pages 1513-1521. 2015.
-
(2015)
NIPS-15
, pp. 1513-1521
-
-
Rothenhäusler, D.1
Heinze, C.2
Peters, J.3
Meinshausen, N.4
-
31
-
-
0003263637
-
Directed cyclic graphical representations of feedback models
-
P. Spirtes. Directed cyclic graphical representations of feedback models. In UAI-95, pages 491-499, 1995.
-
(1995)
UAI-95
, pp. 491-499
-
-
Spirtes, P.1
-
32
-
-
0003614273
-
-
MIT press
-
P. Spirtes, C. Glymour, and R. Scheines. Causation, Prediction, and Search. MIT press, 2000.
-
(2000)
Causation, Prediction, and Search
-
-
Spirtes, P.1
Glymour, C.2
Scheines, R.3
-
33
-
-
0001779012
-
Causal networks: Semantics and expressiveness
-
T.S. Verma and J. Pearl. Causal Networks: Semantics and Expressiveness. UAI-90, 4: 69-76, 1990.
-
(1990)
UAI-90
, vol.4
, pp. 69-76
-
-
Verma, T.S.1
Pearl, J.2
-
34
-
-
52949097616
-
On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias
-
J. Zhang. On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias. Artificial Intelligence, 172(16-17): 1873-1896, 2008.
-
(2008)
Artificial Intelligence
, vol.172
, Issue.16-17
, pp. 1873-1896
-
-
Zhang, J.1
|