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Variational Inference

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TitleStatusHype
Variational Inference via Upper Bound Minimization—0
Differentiable Learning of Submodular Models—0
Context Selection for Embedding ModelsCode0
Variational Deep Q NetworkCode0
The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks—0
On the use of bootstrap with variational inference: Theory, interpretation, and a two-sample test example—0
Variational Inference for Gaussian Process Models with Linear Complexity—0
Diversity-Promoting Bayesian Learning of Latent Variable Models—0
Asymmetric Variational AutoencodersCode0
Variational Adaptive-Newton Method for Explorative Learning—0
Z-Forcing: Training Stochastic Recurrent NetworksCode0
Advances in Variational Inference—0
Message Passing Stein Variational Gradient Descent—0
Alpha-Divergences in Variational Dropout—0
Neural Variational Inference and Learning in Undirected Graphical Models—0
Bayesian model and dimension reduction for uncertainty propagation: applications in random media—0
Convolutional Normalizing FlowsCode0
Structured Variational Inference for Coupled Gaussian Processes—0
Deep Recurrent Gaussian Process with Variational Sparse Spectrum ApproximationCode0
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations—0
Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression—0
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks—0
Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection—0
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference—0
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train DecompositionCode0
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