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Variational Inference

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TitleStatusHype
Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes—0
No-Regret Generative Modeling via Parabolic Monge-Ampère PDE—0
Normalizing flow-based deep variational Bayesian network for seismic multi-hazards and impacts estimation from InSAR imagery—0
Novel Uncertainty Framework for Deep Learning Ensembles—0
On Batch Normalisation for Approximate Bayesian Inference—0
On Divergence Measures for Training GFlowNets—0
One-class Collaborative Filtering with Random Graphs: Annotated Version—0
One Simple Trick to Fix Your Bayesian Neural Network—0
On Implicit Regularization in -VAEs—0
On Implicit Regularization in β-VAEs—0
Online Adaptor Grammars with Hybrid Inference—0
Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling—0
Online Inference for Relation Extraction with a Reduced Feature Set—0
Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems—0
Online Prediction of Dyadic Data with Heterogeneous Matrix Factorization—0
Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar Tracking—0
On PAC-Bayes Bounds for Deep Neural Networks using the Loss Curvature—0
On Representations of Mean-Field Variational Inference—0
On some provably correct cases of variational inference for topic models—0
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes—0
On the Convergence of Black-Box Variational Inference—0
On the Convergence of Coordinate Ascent Variational Inference—0
On the Convergence of Extended Variational Inference for Non-Gaussian Statistical Models—0
On the Convergence of Stochastic Variational Inference in Bayesian Networks—0
On the detrimental effect of invariances in the likelihood for variational inference—0
On the Effectiveness of Mode Exploration in Bayesian Model Averaging for Neural Networks—0
On the Identification of Temporally Causal Representation with Instantaneous Dependence—0
On the Inconsistency of Bayesian Inference for Misspecified Neural Networks—0
On the Information Bottleneck Problems: Models, Connections, Applications and Information Theoretic Views—0
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder—0
On the Out-of-Distribution Coverage of Combining Split Conformal Prediction and Bayesian Deep Learning—0
On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks—0
On the Performance of Direct Loss Minimization for Bayesian Neural Networks—0
On the Relationship Between Active Inference and Control as Inference—0
On importance-weighted autoencoders—0
On the use of bootstrap with variational inference: Theory, interpretation, and a two-sample test example—0
On Variational Inference for User Modeling in Attribute-Driven Collaborative Filtering—0
Operator Variational Inference—0
Probabilistic Control and Majorization of Optimal Control—0
Optimal Control of Complex Systems through Variational Inference with a Discrete Event Decision Process—0
Optimality of variational inference for stochasticblock model with missing links—0
Optimal Lighting Control in Greenhouses Using Bayesian Neural Networks for Sunlight Prediction—0
Optimal lower bounds for logistic log-likelihoods—0
Optimal Transport for Distribution Adaptation in Bayesian Hilbert Maps—0
Outcome-Driven Reinforcement Learning via Variational Inference—0
Overdispersed Black-Box Variational Inference—0
Overpruning in Variational Bayesian Neural Networks—0
PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons—0
Parameters Estimation from the 21 cm signal using Variational Inference—0
Parametric Bootstrap Ensembles as Variational Inference—0
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