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 2201–2226 of 2226 papers

TitleStatusHype
Gaussian Processes for Natural Language Processing—0
Gaussian Process Learning-based Probabilistic Optimal Power Flow—0
Gaussian Process Meta-Representations For Hierarchical Neural Network Weight Priors—0
Gaussian Process Meta-Representations Of Neural Networks—0
Gaussian Process Neurons—0
Gaussian Process Neurons Learn Stochastic Activation Functions—0
Bayesian Inference over the Stiefel Manifold via the Givens Representation—0
General Intelligent Imaging and Uncertainty Quantification by Deterministic Diffusion Model—0
Generalised Bayesian Filtering via Sequential Monte Carlo—0
Generalization Certificates for Adversarially Robust Bayesian Linear Regression—0
Convergence Rates of Variational Inference in Sparse Deep Learning—0
Generalization of generative model for neuronal ensemble inference method—0
Generalized Bayesian Filtering via Sequential Monte Carlo—0
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation—0
Generalized Dropout—0
Robust Bayesian Inference for Moving Horizon Estimation—0
Generalized Power Priors for Improved Bayesian Inference with Historical Data—0
Generalized second law of thermodynamics in the Glosten-Milgrom model—0
Generalizing Eye Tracking With Bayesian Adversarial Learning—0
Generalizing to the Open World: Deep Visual Odometry with Online Adaptation—0
Generative Emergent Communication: Large Language Model is a Collective World Model—0
Generative learning for deep networks—0
Generative Modeling: A Review—0
Generative models and Bayesian inversion using Laplace approximation—0
Accelerated physical emulation of Bayesian inference in spiking neural networks—0
Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models—0
Show:102550
← PrevPage 45 of 45Next →

Benchmark Results

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