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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 501–550 of 2226 papers

TitleStatusHype
Towards a Unified Framework for Sequential Decision Making—0
Statistical physics, Bayesian inference and neural information processing—0
A Mean Field Approach to Empirical Bayes Estimation in High-dimensional Linear Regression—0
A Primer on Bayesian Neural Networks: Review and DebatesCode1
A Metaheuristic for Amortized Search in High-Dimensional Parameter SpacesCode0
Entropic Matching for Expectation Propagation of Markov Jump Processes—0
A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth—0
BayesDLL: Bayesian Deep Learning LibraryCode1
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian ProcessesCode0
Bounded rationality in structured density estimation—0
Bounded rationality in structured density estimation—0
Data-driven Modeling and Inference for Bayesian Gaussian Process ODEs via Double Normalizing FlowsCode0
MFRL-BI: Design of a Model-free Reinforcement Learning Process Control Scheme by Using Bayesian Inference—0
Physics-informed Bayesian inference of external potentials in classical density-functional theory—0
Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided PruningCode1
Reducing the False Positive Rate Using Bayesian Inference in Autonomous Driving Perception—0
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks—0
A Probabilistic Semi-Supervised Approach with Triplet Markov Chains—0
Signatures of Bayesian inference emerge from energy efficient synapsesCode0
Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networksCode0
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks—0
Bayesian inference of composition-dependent phase diagrams—0
PAVI: Plate-Amortized Variational Inference—0
Heterogeneous Multi-Task Gaussian Cox ProcessesCode0
Deep Learning and Bayesian inference for Inverse Problems—0
A transport approach to sequential simulation-based inference—0
Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution—0
Variational Density Propagation Continual Learning—0
On Exact Bayesian Credible Sets for Classification and Pattern Recognition—0
Linking fast and slow: the case for generative models—0
Semi-Implicit Variational Inference via Score MatchingCode0
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental DesignCode0
Accelerated Bayesian imaging by relaxed proximal-point Langevin samplingCode0
Bayesian polynomial neural networks and polynomial neural ordinary differential equations—0
Adaptive mitigation of time-varying quantum noise—0
Natural Evolution Strategies as a Black Box Estimator for Stochastic Variational Inference—0
Monte Carlo guided Diffusion for Bayesian linear inverse problemsCode1
Bayesian Flow NetworksCode2
Gradient-Based Markov Chain Monte Carlo for MIMO Detection—0
A Review of Change of Variable Formulas for Generative Modeling—0
Learning from Topology: Cosmological Parameter Estimation from the Large-scale Structure—0
Pruning a neural network using Bayesian inference—0
A digital twin framework for civil engineering structuresCode0
The Bayesian Context Trees State Space Model for time series modelling and forecasting—0
Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood EstimationCode0
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization ProblemsCode0
A theory of data variability in Neural Network Bayesian inference—0
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty—0
Amortized Variational Inference: When and Why?Code0
A Bayesian Programming Approach to Car-following Model Calibration and Validation using Limited Data—0
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Benchmark Results

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