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Variational Inference

1,952 papers

Papers per year

2
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31
252
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Papers

Inserting Information Bottlenecks for Attribution in Transformers EMNLP 2020
Frequency Bias in Neural Networks for Input of Non-Uniform Density ICML 2020
Model Fusion with Kullback-Leibler Divergence ICML 2020
Provable Smoothness Guarantees for Black-Box Variational Inference ICML 2020
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems ICML 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors ICML 2020
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations ICML 2020
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics ICML 2020
Evaluating Lossy Compression Rates of Deep Generative Models ICML 2020
Meta-Learning with Shared Amortized Variational Inference ICML 2020
Variational Autoencoders with Riemannian Brownian Motion Priors ICML 2020
Variational Inference for Sequential Data with Future Likelihood Estimates ICML 2020
On Implicit Regularization in $β$-VAEs ICML 2020
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective ICML 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020
Learning Robot Skills with Temporal Variational Inference ICML 2020
ControlVAE: Controllable Variational Autoencoder ICML 2020
Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation ICML 2020
Deep Gaussian Markov Random Fields ICML 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables ICML 2020
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020
Amortized Population Gibbs Samplers with Neural Sufficient Statistics ICML 2020
Variational Label Enhancement ICML 2020
Variational Bayesian Quantization ICML 2020