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Bayesian Inference

4,821 papers

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Papers

Thompson Sampling for Unsupervised Sequential Selection ACML 2020
Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection ACML 2020
Localizing and Amortizing: Efficient Inference for Gaussian Processes ACML 2020
Multiplicative Gaussian Particle Filter AISTATS 2020
Asynchronous Gibbs Sampling AISTATS 2020
Non-Parametric Calibration for Classification AISTATS 2020
Uncertainty in Neural Networks: Approximately Bayesian Ensembling AISTATS 2020
Uncertainty Quantification for Sparse Deep Learning AISTATS 2020
Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data AISTATS 2020
Stopping criterion for active learning based on deterministic generalization bounds AISTATS 2020
Accelerated Bayesian Optimisation through Weight-Prior Tuning AISTATS 2020
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization AISTATS 2020
Corruption-Tolerant Gaussian Process Bandit Optimization AISTATS 2020
Simulator Calibration under Covariate Shift with Kernels AISTATS 2020
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning AISTATS 2020
Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020
GP-VAE: Deep Probabilistic Time Series Imputation AISTATS 2020
Validated Variational Inference via Practical Posterior Error Bounds AISTATS 2020
Fixed-confidence guarantees for Bayesian best-arm identification AISTATS 2020
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory AISTATS 2020
Distributionally Robust Bayesian Quadrature Optimization AISTATS 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC AISTATS 2020
On casting importance weighted autoencoder to an EM algorithm to learn deep generative models AISTATS 2020
Deep Structured Mixtures of Gaussian Processes AISTATS 2020
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization AISTATS 2020