← Bayesian & Probabilistic
Machine Learning › Bayesian & Probabilistic ›

Variational Inference

767 directly classified papers

Papers per year

Papers

Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018
Variational Inference based on Robust Divergences AISTATS 2018
Variational Rejection Sampling AISTATS 2018
Variational Sequential Monte Carlo AISTATS 2018
VAE with a VampPrior AISTATS 2018
On Statistical Optimality of Variational Bayes AISTATS 2018
Proximity Variational Inference AISTATS 2018
Stein Variational Message Passing for Continuous Graphical Models ICML 2018
Provable Variational Inference for Constrained Log-Submodular Models NIPS 2018
Heterogeneous Multi-output Gaussian Process Prediction NIPS 2018
Variational Inference with Tail-adaptive f-Divergence NIPS 2018
Simple, Distributed, and Accelerated Probabilistic Programming NIPS 2018
Variational Learning on Aggregate Outputs with Gaussian Processes NIPS 2018
Importance Weighting and Variational Inference NIPS 2018
Uncertainty-Aware Attention for Reliable Interpretation and Prediction NIPS 2018
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis NIPS 2018
Wasserstein Variational Inference NIPS 2018
Hamiltonian Variational Auto-Encoder NIPS 2018
Probabilistic Model-Agnostic Meta-Learning NIPS 2018
Large-Scale Stochastic Sampling from the Probability Simplex NIPS 2018
Transfer of Value Functions via Variational Methods NIPS 2018
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language NIPS 2018
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NIPS 2018
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues NIPS 2018
Bayesian Model-Agnostic Meta-Learning NIPS 2018