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Remco R. Bouckaert
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2020 – today
- 2021
- [j10]Remco R. Bouckaert, Mareike Fischer, Kristina Wicke
:
Combinatorial perspectives on Dollo-k characters in phylogenetics. Adv. Appl. Math. 131: 102252 (2021) - [j9]Jordan Douglas
Adaptive dating and fast proposals: Revisiting the phylogenetic relaxed clock model. PLoS Comput. Biol. 17(2) (2021)
2010 – 2019
- 2019
- [j8]Remco R. Bouckaert
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 15(4) (2019) - [j7]Jing Yang
Bayesian phylodynamics of avian influenza A virus H9N2 in Asia with time-dependent predictors of migration. PLoS Comput. Biol. 15(8) (2019) - 2014
- [j6]Remco R. Bouckaert, Joseph Heled, Denise Kühnert
BEAST 2: A Software Platform for Bayesian Evolutionary Analysis. PLoS Comput. Biol. 10(4) (2014) - 2013
- [i5]Tomas Kocka, Remco R. Bouckaert, Milan Studený:
On characterizing Inclusion of Bayesian Networks. CoRR abs/1301.2282 (2013) - [i4]Enrique F. Castillo, Remco R. Bouckaert, José María Sarabia, Cristina Solares:
Error Estimation in Approximate Bayesian Belief Network Inference. CoRR abs/1302.4934 (2013) - [i3]Remco R. Bouckaert:
Properties of Bayesian Belief Network Learning Algorithms. CoRR abs/1302.6792 (2013) - [i2]Remco R. Bouckaert:
A Stratified Simulation Scheme for Inference in Bayesian Belief Networks. CoRR abs/1302.6793 (2013) - [i1]Remco R. Bouckaert:
Optimizing Causal Orderings for Generating DAGs from Data. CoRR abs/1303.5392 (2013) - 2010
- [j5]Remco R. Bouckaert:
DensiTree: making sense of sets of phylogenetic trees. Bioinform. 26(10): 1372-1373 (2010) - [j4]Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten:
WEKA - Experiences with a Java Open-Source Project. J. Mach. Learn. Res. 11: 2533-2541 (2010) - [j3]Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindner, Milan Studený:
Efficient Algorithms for Conditional Independence Inference. J. Mach. Learn. Res. 11: 3453-3479 (2010)
2000 – 2009
- 2009
- [c22]Remco R. Bouckaert:
A Hierarchical Face Recognition Algorithm. ACML 2009: 38-50 - [c21]Eibe Frank
Conditional Density Estimation with Class Probability Estimators. ACML 2009: 65-81 - 2008
- [c20]Remco R. Bouckaert:
Practical Bias Variance Decomposition. Australasian Conference on Artificial Intelligence 2008: 247-257 - 2007
- [j2]Remco R. Bouckaert, Milan Studený
Racing algorithms for conditional independence inference. Int. J. Approx. Reason. 45(2): 386-401 (2007) - 2006
- [c19]Remco R. Bouckaert:
Efficient AUC Learning Curve Calculation. Australian Conference on Artificial Intelligence 2006: 181-191 - [c18]Remco R. Bouckaert:
Voting Massive Collections of Bayesian Network Classifiers for Data Streams. Australian Conference on Artificial Intelligence 2006: 243-252 - [c17]Remco R. Bouckaert, Michael Goebel, Patricia J. Riddle:
Generalized Unified Decomposition of Ensemble Loss. Australian Conference on Artificial Intelligence 2006: 1133-1139 - [c16]Eibe Frank, Remco R. Bouckaert:
Naive Bayes for Text Classification with Unbalanced Classes. PKDD 2006: 503-510 - 2005
- [c15]Remco R. Bouckaert, Milan Studený
Racing for Conditional Independence Inference. ECSQARU 2005: 221-232 - 2004
- [c14]Remco R. Bouckaert:
Naive Bayes Classifiers That Perform Well with Continuous Variables. Australian Conference on Artificial Intelligence 2004: 1089-1094 - [c13]Remco R. Bouckaert:
Estimating replicability of classifier learning experiments. ICML 2004 - [c12]Remco R. Bouckaert, Eibe Frank:
Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms. PAKDD 2004: 3-12 - 2003
- [c11]Remco R. Bouckaert:
A Probabilistic Line Breaking Algorithm. Australian Conference on Artificial Intelligence 2003: 390-401 - [c10]Remco R. Bouckaert:
Choosing Learning Algorithms Using Sign Tests with High Replicability. Australian Conference on Artificial Intelligence 2003: 710-722 - [c9]Remco R. Bouckaert:
Choosing Between Two Learning Algorithms Based on Calibrated Tests. ICML 2003: 51-58 - 2001
- [c8]Tomás Kocka, Remco R. Bouckaert, Milan Studený:
On characterizing Inclusion of Bayesian Networks. UAI 2001: 261-268
1990 – 1999
- 1996
- [j1]Remco R. Bouckaert, Enrique F. Castillo, José Manuel Gutiérrez
A modified simulation scheme for inference in Bayesian networks. Int. J. Approx. Reason. 14(1): 55-80 (1996) - 1995
- [c7]Remco R. Bouckaert, Milan Studený
Chain graphs: semantics and expressiveness. ECSQARU 1995: 69-76 - [c6]Enrique F. Castillo, Remco R. Bouckaert, José María Sarabia, Cristina Solares:
Error Estimation in Approximate Bayesian Belief Network Inference. UAI 1995: 55-62 - 1994
- [c5]Remco R. Bouckaert:
Properties of Bayesian Belief Network Learning Algorithms. UAI 1994: 102-109 - [c4]Remco R. Bouckaert:
A Stratified Simulation Scheme for Inference in Bayesian Belief Networks. UAI 1994: 110-117 - 1993
- [c3]Remco R. Bouckaert:
Probalistic Network Construction Using the Minimum Description Length Principle. ECSQARU 1993: 41-48 - [c2]Remco R. Bouckaert:
IDAGs: a Perfect Map for Any Distribution. ECSQARU 1993: 49-56 - 1992
- [c1]Remco R. Bouckaert:
Optimizing Causal Orderings for Generating DAGs from Data. UAI 1992: 9-16
Coauthor Index
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