Automatic thesaurus construction using Bayesian networks
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Variational learning in nonlinear Gaussian belief networks
Neural Computation
An Introduction to Variational Methods for Graphical Models
Machine Learning
Experiments of Fast Learning with High Order Boltzmann Machines
Applied Intelligence
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
Applied Intelligence
Deterministic Generative Models for Fast Feature Discovery
Data Mining and Knowledge Discovery
Bayesian parameter estimation via variational methods
Statistics and Computing
A Guide to the Literature on Learning Probabilistic Networks from Data
IEEE Transactions on Knowledge and Data Engineering
Data Categorization Using Decision Trellises
IEEE Transactions on Knowledge and Data Engineering
Training products of experts by minimizing contrastive divergence
Neural Computation
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
HSCC '00 Proceedings of the Third International Workshop on Hybrid Systems: Computation and Control
Pulse-Based Circuits and Methods for Probabilistic Neural Computation
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
Neural representation of probabilistic information
Neural Computation
Collocation map for overcoming data sparseness
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
Reinforcement Learning with Factored States and Actions
The Journal of Machine Learning Research
Information Sciences—Informatics and Computer Science: An International Journal
A Tighter Bound for Graphical Models
Neural Computation
Attractor Dynamics in Feedforward Neural Networks
Neural Computation
Predicting people's bidding behavior in negotiation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A fast learning algorithm for deep belief nets
Neural Computation
Incremental Bayesian networks for structure prediction
Proceedings of the 24th international conference on Machine learning
Hybrid modeling, hmm/nn architectures, and protein applications
Neural Computation
Bayesian networks with a logistic regression model for the conditional probabilities
International Journal of Approximate Reasoning
Training restricted Boltzmann machines using approximations to the likelihood gradient
Proceedings of the 25th international conference on Machine learning
Probabilistic Methods for Financial and Marketing Informatics
Probabilistic Methods for Financial and Marketing Informatics
Using fast weights to improve persistent contrastive divergence
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Herding dynamical weights to learn
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Learning social preferences in games
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Probabilistic Methods for Bioinformatics: with an Introduction to Bayesian Networks
Probabilistic Methods for Bioinformatics: with an Introduction to Bayesian Networks
A latent variable model for generative dependency parsing
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Exploiting contextual independence in probabilistic inference
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Mean field theory for sigmoid belief networks
Journal of Artificial Intelligence Research
Mean-field methods for a special class of belief networks
Journal of Artificial Intelligence Research
Challenge: what is the impact of Bayesian networks on learning?
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
What kind of a graphical model is the brain?
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Local learning in probabilistic networks with hidden variables
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Learning Deep Architectures for AI
Foundations and Trends® in Machine Learning
Neural Networks
Approximate learning in temporal Hidden Hopfield Models
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Deep belief networks are compact universal approximators
Neural Computation
Incremental Sigmoid Belief Networks for Grammar Learning
The Journal of Machine Learning Research
Representing and combining partially specified CPTs
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Learning Bayesian networks with restricted causal interactions
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Variational learning in mixed-state dynamic graphical models
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
IPF for discrete chain factor graphs
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Variational approximations between mean field theory and the junction tree algorithm
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Estimating well-performing bayesian networks using Bernoulli mixtures
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Large deviation methods for approximate probabilistic inference
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Network fragments: representing knowledge for constructing probabilistic models
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Learning Bayesian networks with local structure
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Asymptotic model selection for directed networks with hidden variables*
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Computing upper and lower bounds on likelihoods in intractable networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Bayesian network automata for modelling unbounded structures
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
An efficient learning procedure for deep boltzmann machines
Neural Computation
Fast Structured Prediction Using Large Margin Sigmoid Belief Networks
International Journal of Computer Vision
A unifying probabilistic perspective for spectral dimensionality reduction: insights and new models
The Journal of Machine Learning Research
Multilingual joint parsing of syntactic and semantic dependencies with a latent variable model
Computational Linguistics
The Shape Boltzmann Machine: A Strong Model of Object Shape
International Journal of Computer Vision
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