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variational inference

2069 papers

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Also known as

VI-NET VRNN VBI SVI VIBE VQ-VAE ADVI VARNET MCVI PARVI SAVI VI VAE VMP VB BBVI ELBO VIB

Co-occurring keywords

bayesian inference (1904) gaussian process (1198) generative model (2889) variational autoencoder (1282) latent variable model (564) probabilistic modeling (851) representation learning (6174) uncertainty quantification (1365) latent variable (541) approximate inference (253)

Papers

Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge IJCAI 2020
Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection IJCAI 2020
Scalable Gaussian Process Regression Networks IJCAI 2020
General Purpose MRF Learning with Neural Network Potentials IJCAI 2020
Lifted Hybrid Variational Inference IJCAI 2020
Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model IJCAI 2020
A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning EMNLP 2020
Learning to Learn Kernels with Variational Random Features ICML 2020
Variational Label Enhancement ICML 2020
Thompson Sampling via Local Uncertainty ICML 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables ICML 2020
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions ICML 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
Deep Gaussian Markov Random Fields ICML 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation ICML 2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule ICML 2020
Variational Inference for Sequential Data with Future Likelihood Estimates ICML 2020
Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations ICML 2020
Parametric Gaussian Process Regressors ICML 2020
Meta-Learning with Shared Amortized Variational Inference ICML 2020
A Free-Energy Principle for Representation Learning ICML 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors ICML 2020
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems ICML 2020
Provable Smoothness Guarantees for Black-Box Variational Inference ICML 2020