SOTAVerified

Bayesian Inference

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2101–2125 of 2226 papers

TitleStatusHype
Ensemble Kalman filter for uncertainty in human language comprehension—0
Entropic Matching for Expectation Propagation of Markov Jump Processes—0
Entropy-based Training Methods for Scalable Neural Implicit Sampler—0
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference—0
Epidemic mitigation by statistical inference from contact tracing data—0
E-PINNs: Epistemic Physics-Informed Neural Networks—0
Episodic memory for continual model learning—0
ESG2Risk: A Deep Learning Framework from ESG News to Stock Volatility Prediction—0
ESS-ReduNet: Enhancing Subspace Separability of ReduNet via Dynamic Expansion with Bayesian Inference—0
Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data—0
Estimating Compact Yet Rich Tree Insertion Grammars—0
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning—0
Estimating the impact of non-pharmaceutical interventions and vaccination on the progress of the COVID-19 epidemic in Mexico: a mathematical approach—0
Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data—0
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction—0
Evaluation of Machine Learning Techniques for Green Energy Prediction—0
Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors—0
Event Temporal Relation Extraction with Bayesian Translational Model—0
Evidence of Replica Symmetry Breaking under the Nishimori conditions in epidemic inference on graphs—0
Evolutionary MCMC Sampling and Optimization in Discrete Spaces—0
Exact Bayesian inference for off-line change-point detection in tree-structured graphical models—0
Excess risk analysis for epistemic uncertainty with application to variational inference—0
Exchangeable Variational Autoencoders with Applications to Genomic Data—0
Exoplanet Characterization using Conditional Invertible Neural Networks—0
Expectation Propagation performs a smoothed gradient descent—0
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Benchmark Results

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