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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 401–425 of 2226 papers

TitleStatusHype
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data—0
Modeling human decomposition: a Bayesian approach—0
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps—0
Streaming Bayes GFlowNets—0
Bayesian Calibration of Win Rate Estimation with LLM EvaluatorsCode0
Uncertainty Prediction Neural Network (UpNet): Embedding Artificial Neural Network in Bayesian Inversion Framework to Quantify the Uncertainty of Remote Sensing RetrievalCode0
Bayesian Inference in Recurrent Explicit Duration Switching Linear Dynamical Systems—0
Compositional simulation-based inference for time seriesCode0
Modelling Alzheimer's Protein Dynamics: A Data-Driven Integration of Stochastic Methods, Machine Learning and Connectome Insights—0
Stein Variational Newton Neural Network EnsemblesCode0
Improving Trust Estimation in Human-Robot Collaboration Using Beta Reputation at Fine-grained TimescalesCode0
Interacting Large Language Model Agents. Interpretable Models and Social Learning—0
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data CorruptionsCode0
Constrained Sampling with Primal-Dual Langevin Monte CarloCode0
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs—0
Bayesian Approaches for Revealing Complex Neural Network Dynamics in Parkinson's Disease—0
ELBOing Stein: Variational Bayes with Stein Mixture InferenceCode0
Full-waveform earthquake source inversion using simulation-based inferenceCode0
Variational Bayes Decomposition for Inverse Estimation with Superimposed Multispectral Intensity—0
A Stein Gradient Descent Approach for Doubly Intractable Distributions—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
TRADE: Transfer of Distributions between External Conditions with Normalizing FlowsCode0
FeBiM: Efficient and Compact Bayesian Inference Engine Empowered with Ferroelectric In-Memory Computing—0
Noise-Aware Differentially Private Variational Inference—0
Dimension reduction via score ratio matching—0
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Benchmark Results

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