SOTAVerified

Bayesian Inference

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

Papers

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Showing 1041–1050 of 2226 papers

TitleStatusHype
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs—0
Dynamic Semantic Occupancy Mapping using 3D Scene Flow and Closed-Form Bayesian InferenceCode1
Deep Stable neural networks: large-width asymptotics and convergence rates—0
Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling—0
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning—0
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference—0
Are Bayesian neural networks intrinsically good at out-of-distribution detection?Code0
A Multiple-Instance Learning Approach for the Assessment of Gallbladder Vascularity from Laparoscopic Images—0
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference—0
Neural Variational Gradient DescentCode1
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Benchmark Results

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