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Bayesian Inference

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Papers

Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features AISTATS 2019
Amortized Variational Inference with Graph Convolutional Networks for Gaussian Processes AISTATS 2019
Bernoulli Race Particle Filters AISTATS 2019
Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models AISTATS 2019
Unbiased Smoothing using Particle Independent Metropolis-Hastings AISTATS 2019
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach AISTATS 2019
Doubly Semi-Implicit Variational Inference AISTATS 2019
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference AISTATS 2019
Efficient Bayesian Optimization for Target Vector Estimation AISTATS 2019
Adaptive MCMC via Combining Local Samplers AISTATS 2019
Variational Noise-Contrastive Estimation AISTATS 2019
Improving Quadrature for Constrained Integrands AISTATS 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019
On Theory for BART AISTATS 2019
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models AISTATS 2019
Binary Space Partitioning Forest AISTATS 2019
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019
Database Alignment with Gaussian Features AISTATS 2019
Reparameterizing Distributions on Lie Groups AISTATS 2019
Harmonizable mixture kernels with variational Fourier features AISTATS 2019
Multiscale Gaussian Process Level Set Estimation AISTATS 2019
Efficient Bayes Risk Estimation for Cost-Sensitive Classification AISTATS 2019
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity AISTATS 2019
Ising Models with Latent Conditional Gaussian Variables ALT 2019