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Bayesian Inference

6,267 papers

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Papers

Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees AISTATS 2019 Scalable Global Optimization via Local Bayesian Optimization NeurIPS 2019 Scalable inference of topic evolution via models for latent geometric structures NeurIPS 2019 Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets ICML 2019 Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference NeurIPS 2019 Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NeurIPS 2019 Scalable Thompson Sampling via Optimal Transport AISTATS 2019 Scalable Training of Inference Networks for Gaussian-Process Models ICML 2019 Second-Order Semantic Dependency Parsing with End-to-End Neural Networks ACL 2019 Self-Adversarially Learned Bayesian Sampling AAAI 2019 Semantic Alignment: Finding Semantically Consistent Ground-Truth for Facial Landmark Detection CVPR 2019 Semi-Parametric Sampling for Stochastic Bandits with Many Arms AAAI 2019 Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows AISTATS 2019 Shared Subspace Models for Multi-Group Covariance Estimation JMLR 2019 Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation MLHC 2019 Smoothing Structured Decomposable Circuits NeurIPS 2019 Sparse Variational Inference: Bayesian Coresets from Scratch NeurIPS 2019 Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs NeurIPS 2019 Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping AAAI 2019 Specializing Word Embeddings (for Parsing) by Information Bottleneck EMNLP 2019 SpHMC: Spectral Hamiltonian Monte Carlo AAAI 2019 Statistical Guarantees for the Robustness of Bayesian Neural Networks IJCAI 2019 Statistical Model Aggregation via Parameter Matching NeurIPS 2019 Stein Variational Gradient Descent With Matrix-Valued Kernels NeurIPS 2019 Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NeurIPS 2019