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Variational Inference

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TitleStatusHype
Generalized Variational Continual Learning—0
Parametric Bootstrap Ensembles as Variational Inference—0
Generative Video Compression as Hierarchical Variational Inference—0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Gaussian Density Parametrization Flow: Particle and Stochastic Approaches—0
Scalable Hybrid Hidden Markov Model with Gaussian Process Emission for Sequential Time-series Observations—0
Neural Linear Models with Functional Gaussian Process Priors—0
The Gaussian Process Latent Autoregressive Model—0
Gradient Regularisation as Approximate Variational Inference—0
Rethinking Function-Space Variational Inference in Bayesian Neural Networks—0
On the Inconsistency of Bayesian Inference for Misspecified Neural Networks—0
Marginal Likelihood Gradient for Bayesian Neural Networks—0
Variational Refinement for Importance SamplingUsing the Forward Kullback-Leibler Divergence—0
Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems—0
Variational Laplace for Bayesian neural networks—0
Understanding Variational Inference in Function-SpaceCode0
Recursive Inference for Variational Autoencoders—0
Efficient Variational Inference for Sparse Deep Learning with Theoretical GuaranteeCode0
Dirichlet Pruning for Neural Network CompressionCode0
Sparse within Sparse Gaussian Processes using Neighbor Information—0
Reward Conditioned Neural Movement Primitives for Population Based Variational Policy OptimizationCode0
Multi-output Gaussian Process Modulated Poisson Processes for Event Prediction—0
Quantized Variational InferenceCode0
Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix—0
Amortized Variational Deep Q NetworkCode0
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