Papers
186 papers found
Parameterized Completeness Results for Bayesian Inference
Hans L. Bodlaender, Nils Donselaar, Johan Kwisthout
Recursive autonomy identification-based learning of augmented naive Bayes classifiers
Shouta Sugahara, Wakaba Kishida, Koya Kato et al.
Relevance for Robust Bayesian Network MAP-Explanations
Silja Renooij
Scalable Bayesian Network Structure Learning with Splines
Charupriya Sharma, Peter van Beek
Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers
Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza et al.
The Dual PC Algorithm for Structure Learning
Enrico Giudice, Jack Kuipers, Giusi Moffa
The Functional LiNGAM
Tianle Yang, Joe Suzuki
Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets
Marco Scutari, Christopher Marquis, Laura Azzimonti
Who did it? Identifying the Most Likely Origins of Events
Marcel Gehrke, Ralf Möller, Tanya Braun
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks
Rafael Ballester-Ripoll, Manuele Leonelli
aGrUM/pyAgrum : a toolbox to build models and algorithms
for Probabilistic Graphical Models in Python
Gaspard Ducamp, Christophe Gonzales, Pierre-Henri Wuillemin
Almost No News on the Complexity of MAP in Bayesian Networks
Cassio P. de Campos
An Efficient Low-Rank Tensors Representation for
Algorithms in Complex Probabilistic Graphical Models
Gaspard Ducamp, Philippe Bonnard, Anthony pages = 173-184 Nouy et al.
A New Perspective on Learning Context-Specific Independence
Yujia Shen, Arthur Choi, Adnan Darwiche
Approximating bounded tree-width Bayesian network classifiers with OBDD
Karine Chubarian, György Turán
A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations
Charupriya Sharma, Zhenyu A. Liao, James Cussens et al.
A Software System for Predicting Patient Flow at the Emergency Department of Aalborg University Hospital
Anders L. Madsen, Kristian G. Olesen, Jørn Munkhof Møller et al.
Bayesian Network Model Averaging Classifiers by Subbagging
Shouta Sugahara, Itsuki Aomi, Maomi Ueno
Bayesian network structure learning with causal effects in the presence of latent variables
Kiattikun Chobtham, Anthony C. Constantinou
BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks
Nikolas Bernaola, Mario Michiels, Concha Bielza et al.
Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference
Nazanin Tehrani, Nimar S. Arora, Yucen Lily Li et al.
Building Causal Interaction Models by Recursive Unfolding
L. C. van der Gaag, S. Renooij, A. Facchini
Causal Feature Learning for Utility-Maximizing Agents
David Kinney, David Watson