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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition NIPS 2013
Bayesian entropy estimation for binary spike train data using parametric prior knowledge NIPS 2013
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NIPS 2013
Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization CVPR 2013
Accurate and Robust Registration of Nonrigid Surface Using Hierarchical Statistical Shape Model CVPR 2013
Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models ICML 2013
Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting ICML 2013
Learning the Structure of Sum-Product Networks ICML 2013
Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013
Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013
A Fast and Exact Energy Minimization Algorithm for Cycle MRFs ICML 2013
Inference algorithms for pattern-based CRFs on sequence data ICML 2013
Principal Component Analysis on non-Gaussian Dependent Data ICML 2013
Bayesian nonparametric models for ranked data NIPS 2012
Topic-Partitioned Multinetwork Embeddings NIPS 2012
Learning as MAP Inference in Discrete Graphical Models NIPS 2012
Probabilistic Low-Rank Subspace Clustering NIPS 2012
Learning Probability Measures with respect to Optimal Transport Metrics NIPS 2012
Exponential Concentration for Mutual Information Estimation with Application to Forests NIPS 2012
Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding NIPS 2012
Online Sum-Product Computation Over Trees NIPS 2012
Natural Images, Gaussian Mixtures and Dead Leaves NIPS 2012
Probabilistic acoustic tube: a probabilistic generative model of speech for speech analysis/synthesis AISTATS 2012
Lifted Linear Programming AISTATS 2012
Efficient Sampling from Combinatorial Space via Bridging AISTATS 2012