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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 301–325 of 2226 papers

TitleStatusHype
Accelerated Stein Variational Gradient FlowCode0
DeepRV: pre-trained spatial priors for accelerated disease mapping—0
E-PINNs: Epistemic Physics-Informed Neural Networks—0
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data—0
AutoBayes: A Compositional Framework for Generalized Variational Inference—0
Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models—0
Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems—0
SuperARC: An Agnostic Test for Narrow, General, and Super Intelligence Based On the Principles of Recursive Compression and Algorithmic ProbabilityCode0
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble—0
Simulation-based Bayesian inference under model misspecification—0
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference—0
Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural NetworksCode0
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model—0
How To Make Your Cell Tracker Say "I dunno!"—0
HIF: Height Interval Filtering for Efficient Dynamic Points Removal—0
Efficient Membership Inference Attacks by Bayesian Neural Network—0
Poisoning Bayesian Inference via Data Deletion and Replication—0
Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference—0
Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy—0
Bayesian inference for dynamic spatial quantile models with interactive effects—0
From Understanding the World to Intervening in It: A Unified Multi-Scale Framework for Embodied CognitionCode0
Multi-model Stochastic Particle-based Variational Bayesian Inference for Multiband Delay Estimation—0
Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse—0
Dynamics on Lie groups with applications to attitude estimation—0
AI-Powered Bayesian Inference—0
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Benchmark Results

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