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Variational Inference

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Showing 1651–1700 of 2274 papers

TitleStatusHype
Challenges for BBVI with Normalizing Flows—0
Challenges in Computing and Optimizing Upper Bounds of Marginal Likelihood based on Chi-Square Divergences—0
Channel Estimation in RIS-Enabled mmWave Wireless Systems: A Variational Inference Approach—0
Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach—0
Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders—0
Classification of fNIRS Data Under Uncertainty: A Bayesian Neural Network Approach—0
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors—0
Closed-form Inference and Prediction in Gaussian Process State-Space Models—0
Clustered factor analysis of multineuronal spike data—0
Co-clustering through Optimal Transport—0
CoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage—0
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting—0
Cold Posteriors through PAC-Bayes—0
Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network—0
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems—0
Collapsed variational Bayes for Markov jump processes—0
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review—0
Combining Random Walks and Nonparametric Bayesian Topic Model for Community Detection—0
Comparing the quality of neural network uncertainty estimates for classification problems—0
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation—0
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models—0
Compositional Scene Modeling with Global Object-Centric Representations—0
Computing with Categories in Machine Learning—0
Concurrent Training and Layer Pruning of Deep Neural Networks—0
Composing Normalizing Flows for Inverse Problems—0
Confidence Estimation via Sequential Likelihood Mixing—0
Connection Discovery using Shared Images by Gaussian Relational Topic Model—0
Constrained Bayesian Inference for Low Rank Multitask Learning—0
Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification—0
Constrained Structure Learning for Scene Graph Generation—0
Constraining the Dynamics of Deep Probabilistic Models—0
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning—0
Gaussian Variational State Estimation for Nonlinear State-Space Models—0
Continual Learning with Adaptive Weights (CLAW)—0
Continuous Time Dynamic Topic Models—0
Continuous-time edge modelling using non-parametric point processes—0
Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels—0
Control as Hybrid Inference—0
Convergence of coordinate ascent variational inference for log-concave measures via optimal transport—0
Convergence of Statistical Estimators via Mutual Information Bounds—0
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity—0
Convolutional Normalizing Flows for Deep Gaussian Processes—0
Cooperative Graphical Models—0
Copula variational inference—0
Correcting the Sub-optimal Bit Allocation—0
Correlated Equilibria for Approximate Variational Inference in MRFs—0
Correlated Mixed Membership Modeling of Somatic Mutations—0
Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks—0
Correlated Random Measures—0
Correntropy-Based Improper Likelihood Model for Robust Electrophysiological Source Imaging—0
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