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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 1151–1175 of 2226 papers

TitleStatusHype
EMG Pattern Recognition via Bayesian Inference with Scale Mixture-Based Stochastic Generative Models—0
Mismatched Estimation of rank-one symmetric matrices under Gaussian noiseCode0
Structured Stochastic Gradient MCMCCode0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Compressed Monte Carlo with application in particle filtering—0
Hybrid Bayesian Neural Networks with Functional Probabilistic Layers—0
Bayesian brains and the Rényi divergence—0
Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty—0
Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential EquationsCode0
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks—0
Biases and Variability from Costly Bayesian Inference—0
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on GraphsCode0
Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors—0
Bayesian Nonparametric Modelling for Model-Free Reinforcement Learning in LTE-LAA and Wi-Fi Coexistence—0
InfoNCE is variational inference in a recognition parameterised model—0
q-Paths: Generalizing the Geometric Annealing Path using Power MeansCode0
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence—0
Applications of the Free Energy Principle to Machine Learning and Neuroscience—0
AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data—0
Bayesian Eye Tracking—0
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model—0
Bayesian Neural Networks: Essentials—0
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization—0
Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous DataCode0
Goal-Directed Planning by Reinforcement Learning and Active Inference—0
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Benchmark Results

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