← Bayesian & Probabilistic
Machine Learning › Bayesian & Probabilistic ›

Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Estimating the Size of a Large Network and its Communities from a Random Sample NIPS 2016
On Mixtures of Markov Chains NIPS 2016
Tractable Operations for Arithmetic Circuits of Probabilistic Models NIPS 2016
Consistent Kernel Mean Estimation for Functions of Random Variables NIPS 2016
Statistical Inference for Pairwise Graphical Models Using Score Matching NIPS 2016
Completely random measures for modelling block-structured sparse networks NIPS 2016
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NIPS 2016
Spectral Learning of Dynamic Systems from Nonequilibrium Data NIPS 2016
Edge-exchangeable graphs and sparsity NIPS 2016
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models NIPS 2016
Measuring the reliability of MCMC inference with bidirectional Monte Carlo NIPS 2016
Improving Distributed Word Representation and Topic Model by Word-Topic Mixture Model ACML 2016
Exploring Topic Discriminating Power of Words in Latent Dirichlet Allocation COLING 2016
Rent3D: Floor-Plan Priors for Monocular Layout Estimation CVPR 2015
MCMC Learning COLT 2015
Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices AISTATS 2015
A Topic Modeling Approach to Ranking AISTATS 2015
Fast Classification Rates for High-dimensional Gaussian Generative Models NIPS 2015
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy NIPS 2015
Robust Multi-Image Based Blind Face Hallucination CVPR 2015
Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015
Joint Probabilistic Data Association Revisited ICCV 2015
Gaussian Process Random Fields NIPS 2015
Bounding the Cost of Search-Based Lifted Inference NIPS 2015
Deep Poisson Factor Modeling NIPS 2015