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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 226–250 of 2226 papers

TitleStatusHype
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