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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 251–300 of 2226 papers

TitleStatusHype
A Review of Multiple Try MCMC algorithms for Signal Processing—0
Are you using test log-likelihood correctly?—0
Array Partitioning Based Near-Field Attitude and Location Estimation—0
A sampling-based circuit for optimal decision making—0
A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas—0
A Factor Graph Model of Trust for a Collaborative Multi-Agent System—0
A Bayesian Analysis of Dynamics in Free Recall—0
Bayesian estimation of Differential Transcript Usage from RNA-seq data—0
Approximation Properties of Variational Bayes for Vector Autoregressions—0
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over the Simplex—0
Approximating Permutations with Neural Network Components for Travelling Photographer Problem—0
Adversarial Message Passing For Graphical Models—0
Approximate Inference with the Variational Holder Bound—0
Approximate Inference for Spectral Mixture Kernel—0
A Bayesian model for identifying hierarchically organised states in neural population activity—0
Approximate Gibbs Sampler for Efficient Inference of Hierarchical Bayesian Models for Grouped Count Data—0
Approximate Decentralized Bayesian Inference—0
Advancing Autonomous Vehicle Safety: A Combined Fault Tree Analysis and Bayesian Network Approach—0
Bayesian Differential Privacy through Posterior Sampling—0
Semantic Similarity-Informed Bayesian Borrowing for Quantitative Signal Detection of Adverse Events—0
Bayesian Evolutionary Swarm Architecture: A Formal Epistemic System Grounded in Truth-Based Competition—0
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
Approximate Bayesian inference in spatial environments—0
A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting—0
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale—0
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC—0
Accelerating MCMC via Parallel Predictive Prefetching—0
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification—0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
Approximate Bayesian inference as a gauge theory—0
Accelerating Langevin Sampling with Birth-death—0
Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs—0
Applications of the Free Energy Principle to Machine Learning and Neuroscience—0
Adjoint-aided inference of Gaussian process driven differential equations—0
Bayesian Data Sketching for Varying Coefficient Regression Models—0
Bayesian Deep Learning for Discrete Choice—0
A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series—0
A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation—0
A Distributed Framework for the Construction of Transport Maps—0
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
A Parameter-Free Learning Automaton Scheme—0
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes—0
Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control—0
An Unsupervised Deep Learning Approach for the Wave Equation Inverse Problem—0
An uncertainty-aware Digital Shadow for underground multimodal CO2 storage monitoring—0
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models—0
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks—0
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning—0
Bayesian data fusion with shared priors—0
Bayesian deep learning framework for uncertainty quantification in high dimensions—0
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Benchmark Results

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