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bayesian inference

1904 papers

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Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

Bayesian Generative Active Deep Learning ICML 2019
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations ICML 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations ICML 2019
Understanding and Accelerating Particle-Based Variational Inference ICML 2019
Bayesian Space-Time Partitioning by Sampling and Pruning Spanning Trees JMLR 2019
Dependent relevance determination for smooth and structured sparse regression JMLR 2019
A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization JMLR 2019
Hamiltonian Monte Carlo with Energy Conserving Subsampling JMLR 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space ICML 2019
Rotation Invariant Householder Parameterization for Bayesian PCA ICML 2019
On Asymptotic and Finite-Time Optimality of Bayesian Predictors JMLR 2019
Kernelized Bayesian Softmax for Text Generation NIPS 2019
Exploiting Visual Features Using Bayesian Gated Neural Networks for Disordered Speech Recognition INTERSPEECH 2019
Faster Attend-Infer-Repeat with Tractable Probabilistic Models ICML 2019
Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones UAI 2019
Subspace Inference for Bayesian Deep Learning UAI 2019
Embarrassingly Parallel MCMC using Deep Invertible Transformations UAI 2019
Semi-Supervised Learning of Decision-Making Models for Human-Robot Collaboration CORL 2019
Stochastic Optimal Control as Approximate Input Inference CORL 2019
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions NIPS 2019
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling NIPS 2019
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces NIPS 2019
Switching Linear Dynamics for Variational Bayes Filtering ICML 2019
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Dropout as a Structured Shrinkage Prior ICML 2019