conftrace_
← Machine Learning
Machine Learning ›

Bayesian & Probabilistic

3,963 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,252) Variational Inference (802) Gaussian Processes (570) Bayesian Learning (455) Bayesian Optimization (221) Markov Chain Monte Carlo (143) Nonparametric Bayesian (86) Bayesian Networks (81) Conditional Random Fields (5)

Papers per year

9
118
124
394
151
'05
'10
'15
'20
'25

Papers (including subtopics)

Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016
Grammar induction from (lots of) words alone COLING 2016
End-To-End Saliency Mapping via Probability Distribution Prediction CVPR 2016
Beyond CCA: Moment Matching for Multi-View Models ICML 2016
Relevant sparse codes with variational information bottleneck NIPS 2016
Joint Probabilistic Matching Using m-Best Solutions CVPR 2016
Kernel Mean Shrinkage Estimators JMLR 2016
Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach NIPS 2016
Variational Bayes on Monte Carlo Steroids NIPS 2016
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NIPS 2016
Stochastic Discrete Clenshaw-Curtis Quadrature ICML 2016
Regime Aware Learning PGM 2016
Analysis of Speaker Recognition Systems in Realistic Scenarios of the SITW 2016 Challenge INTERSPEECH 2016
Exploring Differential Topic Models for Comparative Summarization of Scientific Papers COLING 2016
Efficient Computation of Gaussian Process Regression for Large Spatial Data Sets by Patching Local Gaussian Processes JMLR 2016
Hybrid Copula Bayesian Networks PGM 2016
Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016
Double Thompson Sampling for Dueling Bandits NIPS 2016
Stochastic Gradient Geodesic MCMC Methods NIPS 2016
Improving Structure MCMC for Bayesian Networks through Markov Blanket Resampling JMLR 2016
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks PGM 2016
Learning Mixtures of Plackett-Luce Models ICML 2016
Supervised Learning of Acoustic Models in a Zero Resource Setting to Improve DPGMM Clustering INTERSPEECH 2016
Poisson-Gamma dynamical systems NIPS 2016
Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving Processes NIPS 2016