Management Science
Symbolic probabilistic inference with continuous variables
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Bucket elimination: a unifying framework for probabilistic inference
Learning in graphical models
An introduction to variational methods for graphical models
Learning in graphical models
A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
Probabilistic visualisation of high-dimensional binary data
Proceedings of the 1998 conference on Advances in neural information processing systems II
Causal Probabilistic Networks with Both Discrete and Continuous Variables
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulation Approaches to General Probabilistic Inference on Belief Networks
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Variational methods for inference and estimation in graphical models
Variational methods for inference and estimation in graphical models
Variational probabilistic inference and the QMR-DT network
Journal of Artificial Intelligence Research
Implementation of continuous Bayesian networks using sums of weighted Gaussians
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Nonuniform dynamic discretization in hybrid networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
A sufficiently fast algorithm for finding close to optimal junction trees
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
The generalized distributive law
IEEE Transactions on Information Theory
Bayesian networks for discrete multivariate data: an algebraic approach to inference
Journal of Multivariate Analysis
Building Blocks for Variational Bayesian Learning of Latent Variable Models
The Journal of Machine Learning Research
Inference in hybrid Bayesian networks using dynamic discretization
Statistics and Computing
An approach to hybrid probabilistic models
International Journal of Approximate Reasoning
Approximate state estimation in multiagent settings with continuous or large discrete state spaces
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
A machine learning approach for optimal disassembly planning
International Journal of Computer Integrated Manufacturing - THE CHALLENGES OF MANUFACTURING IN THE GLOBALLY INTEGRATED ECONOMY. GUEST EDITOR: ROBIN G. QIU
Latent classification models for binary data
Pattern Recognition
Inference in Hybrid Bayesian Networks with Deterministic Variables
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Inference in hybrid Bayesian networks with mixtures of truncated exponentials
International Journal of Approximate Reasoning
A conceptual model for a value-driven learning healthcare system
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Using test plans for Bayesian modeling
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Inference in hybrid Bayesian networks using mixtures of polynomials
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
International Journal of Computer Vision
Variational approximations between mean field theory and the junction tree algorithm
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Exact inference in networks with discrete children of continuous parents
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Two issues in using mixtures of polynomials for inference in hybrid Bayesian networks
International Journal of Approximate Reasoning
A logic for causal inference in time series with discrete and continuous variables
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
| Hi-index | 0.00 |
We show how to use a variational approximation to the logistic function to perform approximate inference in Bayesian networks containing discrete nodes with continuous parents. Essentially, we convert the logistic function to a Gaussian, which facilitates exact inference, and then iteratively adjust the variational parameters to improve the quality of the approximation. We demonstrate experimentally that this approximation is much faster than sampling, but comparable in accuracy. We also introduce a simple new technique for handling evidence, which allows us to handle arbitrary distributionson observed nodes, as well as achieving a significant speedup in networks with discrete variables of large cardinality.