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Variational Inference

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TitleStatusHype
Approximate Inference for Fully Bayesian Gaussian Process RegressionCode0
Hierarchical Variational Imitation Learning of Control ProgramsCode0
End-to-End Pixel-Based Deep Active Inference for Body Perception and ActionCode0
Variational Metric Scaling for Metric-Based Meta-LearningCode0
Mixture of Inference Networks for VAE-based Audio-visual Speech Enhancement—0
Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines—0
Pseudo-Encoded Stochastic Variational Inference—0
A Closer Look at Disentangling in β-VAE—0
Frequentist Consistency of Generalized Variational Inference—0
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression—0
Solving Bayesian Inverse Problems via Variational Autoencoders—0
Scalable Bayesian Preference Learning for CrowdsCode0
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning—0
Deep Probabilistic Models to Detect Data Poisoning Attacks—0
Stochastic Variational Inference via Upper Bound—0
Efficient Approximate Inference with Walsh-Hadamard Variational Inference—0
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs—0
Differentially Private Federated Variational InferenceCode0
A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multi-Output Gaussian Process ModelCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Continual Learning with Adaptive Weights (CLAW)—0
Exactly Sparse Gaussian Variational Inference with Application to Derivative-Free Batch Nonlinear State Estimation—0
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse—0
Generalized Transformation-based Gradient—0
A Rule for Gradient Estimator Selection, with an Application to Variational Inference—0
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models—0
Statistical Inference in Mean-Field Variational Bayes—0
Amortized Population Gibbs Samplers with Neural Sufficient StatisticsCode0
Neural Topic Model with Reinforcement Learning—0
Unsupervised Neural Machine Translation with Future Rewarding—0
VASE: Variational Assorted Surprise Exploration for Reinforcement Learning—0
Continual Multi-task Gaussian ProcessesCode0
Energy-Inspired Models: Learning with Sampler-Induced DistributionsCode0
Thompson Sampling via Local UncertaintyCode0
Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation—0
Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation—0
Semi-Implicit Stochastic Recurrent Neural Networks—0
Entity Abstraction in Visual Model-Based Reinforcement LearningCode0
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework—0
Implicit Posterior Variational Inference for Deep Gaussian ProcessesCode0
Unifying Variational Inference and PAC-Bayes for Supervised Learning that ScalesCode0
Stabilising priors for robust Bayesian deep learning—0
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems—0
Single Episode Policy Transfer in Reinforcement LearningCode0
Scalable Gradients and Variational Inference for Stochastic Differential Equations—0
Distributional Bayesian optimisation for variational inference on black-box simulatorsCode0
Optimal Transport for Distribution Adaptation in Bayesian Hilbert Maps—0
Structured Semi-Implicit Variational Inference—0
Newtonian Monte Carlo: a second-order gradient method for speeding up MCMC—0
Deep Amortized Variational Inference for Multivariate Time Series Imputation with Latent Gaussian Process Models—0
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