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Variational Inference

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Showing 1551–1600 of 2274 papers

TitleStatusHype
'In-Between' Uncertainty in Bayesian Neural Networks—0
An Unsupervised Bayesian Neural Network for Truth Discovery in Social NetworksCode0
Compound Probabilistic Context-Free Grammars for Grammar InductionCode0
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation—0
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural NetworksCode0
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processesCode0
Disentangled Skill Embeddings for Reinforcement Learning—0
Black-Box Inference for Non-Linear Latent Force Models—0
Provable Gradient Variance Guarantees for Black-Box Variational Inference—0
Second-Order Semantic Dependency Parsing with End-to-End Neural NetworksCode1
vGraph: A Generative Model for Joint Community Detection and Node Representation LearningCode0
Analyses of Multi-collection Corpora via Compound Topic ModelingCode0
Variational Inference with Numerical Derivatives: variance reduction through couplingCode0
Multi-Adversarial Variational Autoencoder Networks—0
Variational Federated Multi-Task Learning—0
Reweighted Expectation MaximizationCode0
Overcoming Mean-Field Approximations in Recurrent Gaussian Process ModelsCode0
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesCode0
Neural Variational Inference For Estimating Uncertainty in Knowledge Graph EmbeddingsCode0
Learning Deep Generative Models with Annealed Importance SamplingCode0
Approximate Variational Inference Based on a Finite Sample of Gaussian Latent VariablesCode0
Coupled Variational Recurrent Collaborative FilteringCode0
Stochastic Neural Network with Kronecker Flow—0
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models—0
Neural Spline FlowsCode1
Note on the bias and variance of variational inferenceCode0
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed StabilityCode0
A Variant of Gaussian Process Dynamical Systems—0
Structured Variational Inference in Continuous Cox Process ModelsCode0
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family ApproximationsCode0
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference—0
Variational Resampling Based Assessment of Deep Neural Networks under Distribution ShiftCode0
Streaming Adaptive Nonparametric Variational Autoencoder—0
Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations—0
Sparse Variational Inference: Bayesian Coresets from ScratchCode0
Practical Deep Learning with Bayesian PrinciplesCode0
Amortized Inference of Variational Bounds for Learning Noisy-OR—0
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial SettingsCode0
Universal Boosting Variational InferenceCode0
Streaming Variational Monte CarloCode0
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning—0
Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process—0
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder—0
Neural Likelihoods for Multi-Output Gaussian Processes—0
Structured Output Learning with Conditional Generative FlowsCode1
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
Efficient EM-Variational Inference for Hawkes Process—0
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational InferenceCode0
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionCode0
Uncertainty-based Continual Learning with Adaptive RegularizationCode0
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