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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 1351–1400 of 2226 papers

TitleStatusHype
Elements of Sequential Monte Carlo—0
Eliciting Language Model Behaviors with Investigator Agents—0
Embarrassingly parallel MCMC using deep invertible transformations—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
EMG Pattern Recognition via Bayesian Inference with Scale Mixture-Based Stochastic Generative Models—0
EMHMM Simulation Study—0
Enhanced gradient-based MCMC in discrete spaces—0
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data—0
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
Experimentally detecting a quantum change point via Bayesian inference—0
Explainable Lane Change Prediction for Near-Crash Scenarios Using Knowledge Graph Embeddings and Retrieval Augmented Generation—0
Exploiting Dynamic Sparsity for Near-Field Spatial Non-Stationary XL-MIMO Channel Tracking—0
Exploiting Reducibility in Unsupervised Dependency Parsing—0
Exploration in Interactive Personalized Music Recommendation: A Reinforcement Learning Approach—0
Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory—0
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference—0
Extending the statistical software package Engine for Likelihood-Free Inference—0
Extension of compressive sampling to binary vector recovery for model-based defect imaging—0
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models—0
Factorized Asymptotic Bayesian Inference for Latent Feature Models—0
False Discovery Rate Control via Frequentist-assisted Horseshoe—0
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models—0
Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks—0
Fast Approximate Inference of Transcript Expression Levels from RNA-seq Data—0
Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation—0
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression—0
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Benchmark Results

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