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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1151–1200 of 2226 papers

TitleStatusHype
Real-Time Part-Based Visual Tracking via Adaptive Correlation Filters—0
Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference—0
Recent advances in deep learning theory—0
Recent methods from statistical inference and machine learning to improve integrative modeling of macromolecular assemblies—0
Recent Progress in Image Deblurring—0
Reciprocally Coupled Local Estimators Implement Bayesian Information Integration Distributively—0
Reconstructing networks with unknown and heterogeneous errors—0
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference—0
Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior—0
Recovering Mental Representations from Large Language Models with Markov Chain Monte Carlo—0
Recursive Metropolis-Hastings Naming Game: Symbol Emergence in a Multi-agent System based on Probabilistic Generative Models—0
Reducing the False Positive Rate Using Bayesian Inference in Autonomous Driving Perception—0
Refining the variational posterior through iterative optimization—0
Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market—0
Regularization by denoising: Bayesian model and Langevin-within-split Gibbs sampling—0
Reinforcement Learning Enhanced PicHunter for Interactive Search—0
Relational Neurosymbolic Markov Models—0
Relative Probability on Finite Outcome Spaces: A Systematic Examination of its Axiomatization, Properties, and Applications—0
Relevance Singular Vector Machine for low-rank matrix sensing—0
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks—0
Reliable ABC model choice via random forests—0
Remarks on kernel Bayes' rule—0
Remote sensing image fusion based on Bayesian GAN—0
Quantifying the mini-batching error in Bayesian inference for Adaptive Langevin dynamics—0
Reparameterization invariance in approximate Bayesian inference—0
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference—0
Representation Learning via Variational Bayesian Networks—0
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference—0
RL with KL penalties is better viewed as Bayesian inference—0
Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data—0
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance—0
Robust Bayesian Inference for Berkson and Classical Measurement Error Models—0
Robust Bayesian Nonnegative Matrix Factorization with Implicit Regularizers—0
SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations—0
Bayesian data-driven discovery of partial differential equations with variable coefficients—0
Robust Energy Storage Scheduling for Imbalance Reduction of Strategically Formed Energy Balancing Groups—0
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications—0
Robust Gaussian Process Regression with Huber Likelihood—0
Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks—0
Roll-back Hamiltonian Monte Carlo—0
Safe-Bayesian Generalized Linear Regression—0
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis—0
Salient Structure Detection by Context-Guided Visual Search—0
Sampling-based Bayesian Inference with gradient uncertainty—0
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability—0
Sampling Bias Correction for Supervised Machine Learning: A Bayesian Inference Approach with Practical Applications—0
Sampling constrained probability distributions using Spherical Augmentation—0
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset—0
Scalable Bayesian inference for the generalized linear mixed model—0
Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified