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Probabilistic Modeling

2,599 papers

Papers per year

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Papers

Variational Gaussian Process Dynamical Systems NIPS 2011
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning NIPS 2011
Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability NIPS 2011
Probabilistic amplitude and frequency demodulation NIPS 2011
A Model for Temporal Dependencies in Event Streams NIPS 2011
Learning unbelievable probabilities NIPS 2011
Kernel Embeddings of Latent Tree Graphical Models NIPS 2011
Selective Prediction of Financial Trends with Hidden Markov Models NIPS 2011
Optimal Reinforcement Learning for Gaussian Systems NIPS 2011
Probabilistic Joint Image Segmentation and Labeling NIPS 2011
An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments NIPS 2011
Solving Decision Problems with Limited Information NIPS 2011
A rational model of causal inference with continuous causes NIPS 2011
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities NIPS 2011
Collective Graphical Models NIPS 2011
Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables AISTATS 2011
Polytope samplers for inference in ill-posed inverse problems AISTATS 2011
Concave Gaussian Variational Approximations for Inference in Large-Scale Bayesian Linear Models AISTATS 2011
Hidden-Unit Conditional Random Fields AISTATS 2011
Mixed Cumulative Distribution Networks AISTATS 2011
Asymptotic Theory for Linear-Chain Conditional Random Fields AISTATS 2011
Kernel Belief Propagation AISTATS 2011
Bayesian Generalized Kernel Mixed Models JMLR 2011
Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Functions on Graphs JMLR 2011
Faster Algorithms for Max-Product Message-Passing JMLR 2011