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Variational Inference

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Showing 1901–1950 of 2274 papers

TitleStatusHype
An Instability in Variational Inference for Topic Models—0
VIBNN: Hardware Acceleration of Bayesian Neural Networks—0
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data—0
Overpruning in Variational Bayesian Neural Networks—0
Topic Modeling on Health Journals with Regularized Variational InferenceCode0
Asynchronous Stochastic Variational Inference—0
Worst-case Optimal Submodular Extensions for Marginal Estimation—0
Generating Neural Networks with Neural NetworksCode0
Learning an Embedding Space for Transferable Robot Skills—0
Structured Exploration via Hierarchical Variational Policy Networks—0
Discrete-Valued Neural Networks Using Variational Inference—0
DropMax: Adaptive Stochastic Softmax—0
An information-theoretic analysis of deep latent-variable models—0
Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational InferenceCode0
Variational Network Quantization—0
DropMax: Adaptive Variational SoftmaxCode0
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in IndiaCode0
Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization—0
Noisy Natural Gradient as Variational InferenceCode0
Exchangeable modelling of relational data: checking sparsity, train-test splitting, and sparse exchangeable Poisson matrix factorizationCode0
Vprop: Variational Inference using RMSprop—0
Collapsed variational Bayes for Markov jump processes—0
Deep Dynamic Poisson Factorization Model—0
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models—0
Tomography of the London Underground: a Scalable Model for Origin-Destination Data—0
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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