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Bayesian Inference

4821 directly classified papers

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Papers

Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018
Hypernetwork-based Implicit Posterior Estimation and Model Averaging of CNN ACML 2018
Batch Normalized Deep Boltzmann Machines ACML 2018
Variational inference for the multi-armed contextual bandit AISTATS 2018
Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018
Robust Locally-Linear Controllable Embedding AISTATS 2018
Factorial HMMs with Collapsed Gibbs Sampling for Optimizing Long-term HIV Therapy AISTATS 2018
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach AISTATS 2018
Tree-based Bayesian Mixture Model for Competing Risks AISTATS 2018
Scalable Bayes via Barycenter in Wasserstein Space JMLR 2018
Constant-Time Predictive Distributions for Gaussian Processes ICML 2018
Tight Regret Bounds for Bayesian Optimization in One Dimension ICML 2018
Learning in Integer Latent Variable Models with Nested Automatic Differentiation ICML 2018
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization ICML 2018
Stagewise Safe Bayesian Optimization with Gaussian Processes ICML 2018
Stein Variational Message Passing for Continuous Graphical Models ICML 2018
Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes JMLR 2018
Scaling up Data Augmentation MCMC via Calibration JMLR 2018
ELFI: Engine for Likelihood-Free Inference JMLR 2018
Patchwork Kriging for Large-scale Gaussian Process Regression JMLR 2018
Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression JMLR 2018
Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation JMLR 2018
Principled Selection of Hyperparameters in the Latent Dirichlet Allocation Model JMLR 2018
Variational Fourier Features for Gaussian Processes JMLR 2018
A sum-product algorithm with polynomials for computing exact derivatives of the likelihood in Bayesian networks PGM 2018