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Variational Inference

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TitleStatusHype
Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions—0
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels—0
uniblock: Scoring and Filtering Corpus with Unicode Block InformationCode0
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning—0
Hierarchical Bayesian Personalized Recommendation: A Case Study and Beyond—0
Learning document embeddings along with their uncertaintiesCode0
Semi-Implicit Graph Variational Auto-EncodersCode0
Unconstrained Monotonic Neural NetworksCode0
To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics—0
Convergence Rates of Variational Inference in Sparse Deep Learning—0
Probabilistic Models with Deep Neural NetworksCode0
Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks—0
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference—0
On importance-weighted autoencoders—0
Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function—0
Towards Verified Stochastic Variational Inference for Probabilistic ProgramsCode0
D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction—0
Subspace Inference for Bayesian Deep LearningCode0
Structured Variational Inference in Unstable Gaussian Process State Space ModelsCode0
The Dynamic Embedded Topic ModelCode0
Trust-Region Variational Inference with Gaussian Mixture Models—0
Interpretable Dynamics Models for Data-Efficient Reinforcement Learning—0
Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data—0
Variational Inference MPC for Bayesian Model-based Reinforcement Learning—0
Neuron ranking -- an informed way to condense convolutional neural networks architecture—0
Learning GPLVM with arbitrary kernels using the unscented transformationCode0
Deep Bayesian Natural Language Processing—0
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep LearningCode0
The Thermodynamic Variational ObjectiveCode0
Empirical Study of the Benefits of Overparameterization in Learning Latent Variable ModelsCode0
'In-Between' Uncertainty in Bayesian Neural Networks—0
An Unsupervised Bayesian Neural Network for Truth Discovery in Social NetworksCode0
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation—0
Compound Probabilistic Context-Free Grammars for Grammar InductionCode0
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural NetworksCode0
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processesCode0
Black-Box Inference for Non-Linear Latent Force Models—0
Disentangled Skill Embeddings for Reinforcement Learning—0
Provable Gradient Variance Guarantees for Black-Box Variational Inference—0
vGraph: A Generative Model for Joint Community Detection and Node Representation LearningCode0
Variational Inference with Numerical Derivatives: variance reduction through couplingCode0
Analyses of Multi-collection Corpora via Compound Topic ModelingCode0
Multi-Adversarial Variational Autoencoder Networks—0
Variational Federated Multi-Task Learning—0
Overcoming Mean-Field Approximations in Recurrent Gaussian Process ModelsCode0
Reweighted Expectation MaximizationCode0
Learning Deep Generative Models with Annealed Importance SamplingCode0
Neural Variational Inference For Estimating Uncertainty in Knowledge Graph EmbeddingsCode0
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesCode0
Coupled Variational Recurrent Collaborative FilteringCode0
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