SOTAVerified

Variational Inference

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1351–1400 of 2274 papers

TitleStatusHype
Cluster-based Regression using Variational Inference and Applications in Financial Forecasting—0
Forward Amortized Inference for Likelihood-Free Variational Marginalization—0
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space—0
Forward χ^2 Divergence Based Variational Importance Sampling—0
Foundation Posteriors for Approximate Probabilistic Inference—0
Frequentist Consistency of Generalized Variational Inference—0
From MAP to Marginals: Variational Inference in Bayesian Submodular Models—0
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models—0
FUNCK: Information Funnels and Bottlenecks for Invariant Representation Learning—0
Functional Complexity-adaptive Temporal Tensor Decomposition—0
Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis—0
Functional Stochastic Gradient MCMC for Bayesian Neural Networks—0
Functional Variational Inference based on Stochastic Process Generators—0
Function-Space Regularization for Deep Bayesian Classification—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models—0
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework—0
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence—0
Gamma Processes, Stick-Breaking, and Variational Inference—0
Gauging Variational Inference—0
Gaussian Density Parametrization Flow: Particle and Stochastic Approaches—0
Gaussian Mean Field Regularizes by Limiting Learned Information—0
Gaussian Process Conditional Density Estimation—0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Gaussian Process Meta-Representations Of Neural Networks—0
Gaussian Process Tilted Nonparametric Density Estimation using Fisher Divergence Score Matching—0
Generalised Gaussian Process Latent Variable Models (GPLVM) with Stochastic Variational Inference—0
Convergence Rates of Variational Inference in Sparse Deep Learning—0
Generalized Transformation-based Gradient—0
Generalized Variational Continual Learning—0
Generating Diverse Translation from Model Distribution with Dropout—0
Generative Flow Networks: Theory and Applications to Structure Learning—0
Generative Modeling of Neural Dynamics via Latent Stochastic Differential Equations—0
Generative Models for Learning from Crowds—0
Generative Particle Variational Inference via Estimation of Functional Gradients—0
Generative Temporal Models with Memory—0
Generative Video Compression as Hierarchical Variational Inference—0
Geometric Dirichlet Means algorithm for topic inference—0
Geometric variational inference—0
GFlowOut: Dropout with Generative Flow Networks—0
Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes—0
Good Initializations of Variational Bayes for Deep Models—0
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models—0
GRADE: Graph Dynamic Embedding—0
Gradient-based inference of abstract task representations for generalization in neural networks—0
Variational Laplace for Bayesian neural networks—0
Gradient Regularisation as Approximate Variational Inference—0
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows—0
PGODE: Towards High-quality System Dynamics Modeling—0
Neural Graph Collaborative Filtering Using Variational Inference—0
Show:102550
← PrevPage 28 of 46Next →

No leaderboard results yet.