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 276–300 of 2226 papers

TitleStatusHype
Fast Burst-Sparsity Learning Approach for Massive MIMO-OTFS Channel Estimation—0
Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise—0
InVAErt networks for amortized inference and identifiability analysis of lumped parameter hemodynamic modelsCode0
Value of Information and Reward Specification in Active Inference and POMDPs—0
Bayesian inference to improve quality of Retrieval Augmented Generation—0
Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations—0
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithmCode1
Exchangeable Sequence Models Quantify Uncertainty Over Latent Concepts—0
Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretability—0
Meta-Posterior Consistency for the Bayesian Inference of Metastable System—0
Identification and Inference for Synthetic Control Methods with Spillover Effects: Estimating the Economic Cost of the Sudan Split—0
Persistent Sampling: Enhancing the Efficiency of Sequential Monte CarloCode1
Neural Surrogate HMC: Accelerated Hamiltonian Monte Carlo with a Neural Network Surrogate Likelihood—0
Variational Inference Using Material Point Method—0
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection—0
Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems—0
Subspace Constrained Variational Bayesian Inference for Structured Compressive Sensing with a Dynamic Grid—0
Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals—0
SoftCVI: Contrastive variational inference with self-generated soft labelsCode0
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation—0
Variation Bayesian Interference for Multiple Extended Targets or Unresolved Group Targets Tracking—0
Improving Graph Out-of-distribution Generalization on Real-world Data—0
Variational Inference via Smoothed Particle Hydrodynamics—0
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based ModelsCode0
FedLog: Personalized Federated Classification with Less Communication and More Flexibility—0
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Benchmark Results

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