SOTAVerified

Bayesian Inference

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

Papers

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Showing 601–625 of 2226 papers

TitleStatusHype
AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data—0
A Mathematical Walkthrough and Discussion of the Free Energy Principle—0
Biologically Inspired Dynamic Textures for Probing Motion Perception—0
Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery—0
Blindness of score-based methods to isolated components and mixing proportions—0
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs—0
Body movement to sound interface with vector autoregressive hierarchical hidden Markov models—0
Bone fusion in normal and pathological development is constrained by the network architecture of the human skull—0
Bootstrapped synthetic likelihood—0
Bounded rationality in structured density estimation—0
Bounded rationality in structured density estimation—0
Bridging the reality gap in quantum devices with physics-aware machine learning—0
Bridging the Sim-to-Real Gap with Bayesian Inference—0
Automatic maneuver detection and tracking of space objects in optical survey scenarios based on stochastic hybrid systems formulation—0
Biogeochemistry-Informed Neural Network (BINN) for Improving Accuracy of Model Prediction and Scientific Understanding of Soil Organic Carbon—0
A Unified Kernel for Neural Network Learning—0
Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems—0
Building general Langevin models from discrete data sets—0
Burn-in, bias, and the rationality of anchoring—0
Automatic Variational Inference in Stan—0
Calibrating Agent-based Models to Microdata with Graph Neural Networks—0
Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution—0
A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting—0
Calibration and Filtering of Exponential L\'evy Option Pricing Models—0
A Markov Model of Machine Translation using Non-parametric Bayesian Inference—0
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Benchmark Results

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