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← Bayesian & Probabilistic
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Bayesian & Probabilistic
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Bayesian Networks
81 directly classified papers
Papers per year
2005: 1
2006: 1
2007: 2
2008: 3
2009: 2
2010: 5
2011: 2
2012: 2
2013: 3
2014: 6
2015: 3
2016: 2
2017: 2
2018: 6
2019: 12
2020: 7
2021: 8
2022: 5
2023: 3
2024: 4
2025: 2
Papers
Learnability of Parameter-Bounded Bayes Nets
AAAI 2025
Decomposed Quadratization: Efficient QUBO Formulation for Learning Bayesian Network
AAAI 2025
Surrogate Bayesian Networks for Approximating Evolutionary Games
AISTATS 2024
The Virtual Driving Instructor: Multi-Agent System Collaborating via Knowledge Graph for Scalable Driver Education
AAAI 2024
Interventional Causal Discovery in a Mixture of DAGs
NIPS 2024
Learning Bayesian Network Classifiers to Minimize the Class Variable Parameters
AAAI 2024
Kalman Bayesian Neural Networks for Closed-Form Online Learning
AAAI 2023
Bayesian Federated Neural Matching That Completes Full Information
AAAI 2023
Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks
AAAI 2023
Towards Federated Bayesian Network Structure Learning with Continuous Optimization
AISTATS 2022
Efficient Causal Structure Learning from Multiple Interventional Datasets with Unknown Targets
AAAI 2022
Hedging as Reward Augmentation in Probabilistic Graphical Models
NIPS 2022
Independence Testing for Bounded Degree Bayesian Networks
NIPS 2022
Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics
AAAI 2022
Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification
NIPS 2021
Learning Fast-Inference Bayesian Networks
NIPS 2021
Efficient Bayesian Network Structure Learning via Parameterized Local Search on Topological Orderings
AAAI 2021
Learning the Parameters of Bayesian Networks from Uncertain Data
AAAI 2021
Improving Causal Discovery By Optimal Bayesian Network Learning
AAAI 2021
DiBS: Differentiable Bayesian Structure Learning
NIPS 2021
Turbocharging Treewidth-Bounded Bayesian Network Structure Learning
AAAI 2021
Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases
NIPS 2021
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
NIPS 2020
Label Error Correction and Generation through Label Relationships
AAAI 2020
Towards Interpretable Clinical Diagnosis with Bayesian Network Ensembles Stacked on Entity-Aware CNNs
ACL 2020
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