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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 201–250 of 2226 papers

TitleStatusHype
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
Constrained Sampling with Primal-Dual Langevin Monte CarloCode0
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data CorruptionsCode0
Bayesian Approaches for Revealing Complex Neural Network Dynamics in Parkinson's Disease—0
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs—0
Full-waveform earthquake source inversion using simulation-based inferenceCode0
ELBOing Stein: Variational Bayes with Stein Mixture InferenceCode0
Variational Bayes Decomposition for Inverse Estimation with Superimposed Multispectral Intensity—0
A Stein Gradient Descent Approach for Doubly Intractable Distributions—0
BSD: a Bayesian framework for parametric models of neural spectraCode2
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Dimension reduction via score ratio matching—0
FeBiM: Efficient and Compact Bayesian Inference Engine Empowered with Ferroelectric In-Memory Computing—0
TRADE: Transfer of Distributions between External Conditions with Normalizing FlowsCode0
Noise-Aware Differentially Private Variational Inference—0
Conditional diffusions for amortized neural posterior estimationCode0
Scalable Random Feature Latent Variable ModelsCode1
A Bayesian Perspective on the Maximum Score Problem—0
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation—0
BI-EqNO: Generalized Approximate Bayesian Inference with an Equivariant Neural Operator Framework—0
A Trust-Region Method for Graphical Stein Variational Inference—0
Semiparametric Bayesian Inference for a Conditional Moment Equality Model—0
On Cold Posteriors of Probabilistic Neural Networks: Understanding the Cold Posterior Effect and A New Way to Learn Cold Posteriors with Tight Generalization GuaranteesCode0
A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice—0
Goal Inference from Open-Ended Dialog—0
Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform InversionCode0
Active inference and deep generative modeling for cognitive ultrasound—0
Bayesian inference of mixed Gaussian phylogenetic modelsCode0
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation MatrixCode0
Optimal lower bounds for logistic log-likelihoods—0
A Variational Bayesian Inference Theory of Elasticity and Its Mixed Probabilistic Finite Element Method for Inverse Deformation Solutions in Any Dimension—0
Efficient Reinforcement Learning with Large Language Model Priors—0
On the Minimal Theory of Consciousness Implicit in Active Inference—0
Efficient Weight-Space Laplace-Gaussian Filtering and Smoothing for Sequential Deep Learning—0
TapType: Ten-finger text entry on everyday surfaces via Bayesian inference—0
Ranking Policy Learning via Marketplace Expected Value Estimation From Observational Data—0
Improving Generalization with Flat Hilbert Bayesian Inference—0
Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network ApproachCode0
The Benefit of Being Bayesian in Online Conformal PredictionCode0
An uncertainty-aware Digital Shadow for underground multimodal CO2 storage monitoring—0
Thermodynamic Bayesian Inference—0
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active InferenceCode0
Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions—0
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Benchmark Results

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