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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
Analogy as Nonparametric Bayesian Inference over Relational Systems—0
Linguists Who Use Probabilistic Models Love Them: Quantification in Functional Distributional Semantics—0
Bayesian Adversarial Human Motion SynthesisCode1
Variational Bayesian Inference for Crowdsourcing Predictions—0
Adaptive quadrature schemes for Bayesian inference via active learning—0
QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision—0
Probabilistic Object Classification using CNN ML-MAP layers—0
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics—0
Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis—0
Model Evidence with Fast Tree Based QuadratureCode0
Is there a wave excitation in the Thalamus?—0
Simulation-Based Inference for Global Health DecisionsCode2
Variational Inference as Iterative Projection in a Bayesian Hilbert Space with Application to Robotic State Estimation—0
On Kalman-Bucy filters, linear quadratic control and active inferenceCode0
Building general Langevin models from discrete data sets—0
Data-Driven Verification under Signal Temporal Logic Constraints—0
Amortized Bayesian Inference for Models of Cognition—0
ESG2Risk: A Deep Learning Framework from ESG News to Stock Volatility Prediction—0
Bayesian inference of infected patients in group testing with prevalence estimationCode0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
The Two Kinds of Free Energy and the Bayesian RevolutionCode0
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence—0
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck—0
Practical calibration of the temperature parameter in Gibbs posteriorsCode0
Gaussian Process Learning-based Probabilistic Optimal Power Flow—0
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
Bayesian Consensus: Consensus Estimates from Miscalibrated Instruments under Heteroscedastic Noise—0
Scaling Bayesian inference of mixed multinomial logit models to very large datasets—0
Model Uncertainty Quantification for Reliable Deep Vision Structural Health Monitoring—0
Active recursive Bayesian inference using Rényi information measures—0
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
The equivalence between Stein variational gradient descent and black-box variational inference—0
Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market—0
Inferring COVID-19 spreading rates and potential change points for case number forecastsCode1
Supervised Learning with Quantum MeasurementsCode1
Bayesian ODE Solvers: The Maximum A Posteriori Estimate—0
GAN-based Priors for Quantifying UncertaintyCode1
Too many cooks: Bayesian inference for coordinating multi-agent collaborationCode1
A Bayesian brain model of adaptive behavior: An application to the Wisconsin Card Sorting Task—0
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of componentsCode0
BayesFlow: Learning complex stochastic models with invertible neural networksCode1
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods—0
The Variational InfoMax Learning Objective—0
Deep Active Inference for Autonomous Robot Navigation—0
A Bayesian algorithm for retrosynthesisCode1
Flexible Bayesian Nonlinear Model ConfigurationCode1
MPC-guided Imitation Learning of Neural Network Policies for the Artificial PancreasCode0
PlaNet of the Bayesians: Reconsidering and Improving Deep Planning Network by Incorporating Bayesian Inference—0
MC^2RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference—0
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Benchmark Results

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