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 1451–1500 of 2226 papers

TitleStatusHype
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks—0
Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles—0
Fundamental Linear Algebra Problem of Gaussian Inference—0
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models—0
GAN priors for Bayesian inference—0
Gaussian Density Parametrization Flow: Particle and Stochastic Approaches—0
Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation—0
Gaussian Process-based Spatial Reconstruction of Electromagnetic fields—0
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
Geometric Ergodicity in Modified Variations of Riemannian Manifold and Lagrangian Monte Carlo—0
Geometry of Score Based Generative Models—0
GFlowOut: Dropout with Generative Flow Networks—0
Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes—0
Global seismic monitoring as probabilistic inference—0
Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory—0
Goal-directed decision making in prefrontal cortex: a computational framework—0
Goal-Directed Planning by Reinforcement Learning and Active Inference—0
Goal Inference from Open-Ended Dialog—0
Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration—0
Godot is not coming: when we will let innovations enter psychiatry?—0
Good Initializations of Variational Bayes for Deep Models—0
GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model—0
Gradient-Based Markov Chain Monte Carlo for MIMO Detection—0
Graph Tracking in Dynamic Probabilistic Programs via Source Transformations—0
Guess Who's Coming (and Who's Going): Bringing Perspective to the Rational Speech Acts Framework—0
Show:102550
← PrevPage 30 of 45Next →

Benchmark Results

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