SOTAVerified

Bayesian Inference

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

Papers

Showing 19261950 of 2226 papers

TitleStatusHype
Calibrating Agent-based Models to Microdata with Graph Neural Networks0
Calibration and Filtering of Exponential L\'evy Option Pricing Models0
Calibration and Uncertainty Quantification of Bayesian Convolutional Neural Networks for Geophysical Applications0
Calibration of Model Uncertainty for Dropout Variational Inference0
Can Bayesian Neural Networks Make Confident Predictions?0
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference0
Canonical Cortical Circuits and the Duality of Bayesian Inference and Optimal Control0
Can Sequential Bayesian Inference Solve Continual Learning?0
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning0
Cascaded Calibration of Mechatronic Systems via Bayesian Inference0
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models0
Causal Inference through a Witness Protection Program0
Predictive Coding beyond Correlations0
Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems0
Chance, long tails, and inference: a non-Gaussian, Bayesian theory of vocal learning in songbirds0
Characteristics of Monte Carlo Dropout in Wide Neural Networks0
Classified as unknown: A novel Bayesian neural network0
Clustered Mallows Model0
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach0
Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI0
Coherent Track-Before-Detect0
Cohort effects in mortality modelling: a Bayesian state-space approach0
Cold Posteriors through PAC-Bayes0
Collapsed Variational Bayesian Inference for PCFGs0
Bayesian Analysis of Combinatorial Gaussian Process Bandits0
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Benchmark Results

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