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Probabilistic Modeling

2,252 papers

Papers per year

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Papers

Empirical models of spiking in neural populations NIPS 2011
Robust Multi-Class Gaussian Process Classification NIPS 2011
t-divergence Based Approximate Inference NIPS 2011
Inverting Grice's Maxims to Learn Rules from Natural Language Extractions NIPS 2011
Expressive Power and Approximation Errors of Restricted Boltzmann Machines NIPS 2011
Information Rates and Optimal Decoding in Large Neural Populations NIPS 2011
A Global Structural EM Algorithm for a Model of Cancer Progression NIPS 2011
Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NIPS 2011
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials NIPS 2011
Probabilistic amplitude and frequency demodulation NIPS 2011
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NIPS 2011
Learning unbelievable probabilities NIPS 2011
Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines NIPS 2011
On Causal Discovery with Cyclic Additive Noise Models 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
Group Anomaly Detection using Flexible Genre Models NIPS 2011
Probabilistic Joint Image Segmentation and Labeling NIPS 2011
An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments NIPS 2011
Demixed Principal Component Analysis NIPS 2011
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron NIPS 2011
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities NIPS 2011
Collective Graphical Models NIPS 2011
Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization ACML 2011