← Bayesian & Probabilistic
Artificial Intelligence › Bayesian & Probabilistic ›

Probabilistic Modeling

2591 directly classified papers

Papers per year

Papers

Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013
Learning Linear Bayesian Networks with Latent Variables ICML 2013
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models ICML 2013
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks ICML 2013
A non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines ICML 2013
On learning parametric-output HMMs ICML 2013
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks NIPS 2013
Learning to Pass Expectation Propagation Messages NIPS 2013
Optimal integration of visual speed across different spatiotemporal frequency channels NIPS 2013
Conditional Random Fields via Univariate Exponential Families NIPS 2013
When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity NIPS 2013
Restricting exchangeable nonparametric distributions NIPS 2013
On Poisson Graphical Models NIPS 2013
Robust Low Rank Kernel Embeddings of Multivariate Distributions NIPS 2013
Approximate Inference in Continuous Determinantal Processes NIPS 2013
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture NIPS 2013
Modeling Overlapping Communities with Node Popularities NIPS 2013
Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests NIPS 2013
A simple example of Dirichlet process mixture inconsistency for the number of components NIPS 2013
Approximate inference in latent Gaussian-Markov models from continuous time observations NIPS 2013
Summary Statistics for Partitionings and Feature Allocations NIPS 2013
Context-sensitive active sensing in humans NIPS 2013
First-order Decomposition Trees NIPS 2013
Multi-Task Bayesian Optimization NIPS 2013
A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data NIPS 2013