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Variational Inference

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TitleStatusHype
Generative Particle Variational Inference via Estimation of Functional Gradients—0
Generative Models for Learning from Crowds—0
Generative Modeling of Neural Dynamics via Latent Stochastic Differential Equations—0
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review—0
A Tutorial on the Mathematical Model of Single Cell Variational Inference—0
Variational inference of fractional Brownian motion with linear computational complexity—0
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis—0
Generative Flow Networks: Theory and Applications to Structure Learning—0
A Tutorial on Sparse Gaussian Processes and Variational Inference—0
Generating Diverse Translation from Model Distribution with Dropout—0
Collapsed variational Bayes for Markov jump processes—0
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems—0
A Tutorial on Parametric Variational Inference—0
Generalized Variational Continual Learning—0
Generalized Transformation-based Gradient—0
Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network—0
Convergence Rates of Variational Inference in Sparse Deep Learning—0
Generalised Gaussian Process Latent Variable Models (GPLVM) with Stochastic Variational Inference—0
Cold Posteriors through PAC-Bayes—0
A Tutorial on Deep Latent Variable Models of Natural Language—0
Gaussian Process Tilted Nonparametric Density Estimation using Fisher Divergence Score Matching—0
Gaussian Process Meta-Representations Of Neural Networks—0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification—0
A Mathematical Walkthrough and Discussion of the Free Energy Principle—0
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting—0
Gaussian Process Conditional Density Estimation—0
Gaussian Mean Field Regularizes by Limiting Learned Information—0
A trust-region method for stochastic variational inference with applications to streaming data—0
Gaussian Density Parametrization Flow: Particle and Stochastic Approaches—0
Gauging Variational Inference—0
Gamma Processes, Stick-Breaking, and Variational Inference—0
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence—0
CoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage—0
A Trust-Region Method for Graphical Stein Variational Inference—0
-VAEs : Optimising variational inference by learning data-dependent divergence skew—0
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework—0
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models—0
Co-clustering through Optimal Transport—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Function-Space Regularization for Deep Bayesian Classification—0
Clustered factor analysis of multineuronal spike data—0
AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond—0
Functional Variational Inference based on Stochastic Process Generators—0
Closed-form Inference and Prediction in Gaussian Process State-Space Models—0
Functional Stochastic Gradient MCMC for Bayesian Neural Networks—0
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors—0
Atmospheric Turbulence Correction via Variational Deep Diffusion—0
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics—0
A deep generative model for single-cell RNA sequencing with application to detecting differentially expressed genes—0
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