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Variational Inference

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Showing 1851–1900 of 2274 papers

TitleStatusHype
Fast Dual Variational Inference for Non-Conjugate LGMs—0
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions—0
Faster variational inducing input Gaussian process classification—0
Fast moment estimation for generalized latent Dirichlet models—0
Fast nonparametric clustering of structured time-series—0
Fast Second-Order Stochastic Backpropagation for Variational Inference—0
Fast Second Order Stochastic Backpropagation for Variational Inference—0
Fast Variational Inference for Large-scale Internet Diagnosis—0
Fast variational Bayes methods for multinomial probit models—0
Fast Variational Inference in the Conjugate Exponential Family—0
Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows—0
Favour: FAst Variance Operator for Uncertainty Rating—0
f-Divergence Thermodynamic Variational Objective: a Deformed Geometry Perspective—0
f-Divergence Variational Inference—0
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes—0
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models—0
Federated Empirical Risk Minimization via Second-Order Method—0
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework—0
Federated Learning with Decoupled Probabilistic-Weighted Gradient Aggregation—0
Federated Variational Inference for Bayesian Mixture Models—0
Federated Variational Inference Methods for Structured Latent Variable Models—0
Federated Variational Inference: Towards Improved Personalization and Generalization—0
FedHB: Hierarchical Bayesian Federated Learning—0
Few-sample Variational Inference of Bayesian Neural Networks with Arbitrary Nonlinearities—0
Few Shot Activity Recognition Using Variational Inference—0
FEW-SHOTLEARNING WITH WEAK SUPERVISION—0
FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation—0
Flat Seeking Bayesian Neural Networks—0
Flexible Modeling of Latent Task Structures in Multitask Learning—0
Flow-based Recurrent Belief State Learning for POMDPs—0
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering—0
Bayesian evidence estimation from posterior samples with normalizing flows—0
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
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