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 351–400 of 2226 papers

TitleStatusHype
Network reconstruction via the minimum description length principle—0
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
Variational Neuron Shifting for Few-Shot Image Classification Across Domains—0
RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models—0
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design—0
Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks—0
Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing ConstantsCode0
Accurate Direct Positioning in Distributed MIMO Using Delay-Doppler Channel Measurements—0
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential EquationsCode1
Variational Bayesian surrogate modelling with application to robust design optimisation—0
Uncertainty in latent representations of variational autoencoders optimized for visual tasksCode0
Scalable Data Assimilation with Message PassingCode0
Underdetermined DOA Estimation of Off-Grid Sources Based on the Generalized Double Pareto Prior—0
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models—0
Neural Methods for Amortized Inference—0
Aligning language models with human preferencesCode2
Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference—0
Analytical Approximation of the ELBO Gradient in the Context of the Clutter ProblemCode0
All-in-one simulation-based inferenceCode2
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learningCode0
Bayesian Federated Model Compression for Communication and Computation Efficiency—0
Interactive Learning of Physical Object Properties Through Robot Manipulation and Database of Object MeasurementsCode0
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks—0
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear RegressionCode0
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation—0
Accounting for contact network uncertainty in epidemic inferences—0
Divide, Conquer, Combine Bayesian Decision Tree Sampling—0
A Unified Kernel for Neural Network Learning—0
Bridging the Sim-to-Real Gap with Bayesian Inference—0
Bridging Privacy and Robustness for Trustworthy Machine Learning—0
Predictive, scalable and interpretable knowledge tracing on structured domainsCode0
Clustered Mallows Model—0
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware PriorsCode0
Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappingsCode0
Scalable Spatiotemporal Prediction with Bayesian Neural FieldsCode2
In-context Exploration-Exploitation for Reinforcement Learning—0
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
Scalable Bayesian inference for the generalized linear mixed model—0
A prediction rigidity formalism for low-cost uncertainties in trained neural networks—0
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming—0
Statistical Mechanics of Dynamical System Identification—0
Listening to the Noise: Blind Denoising with Gibbs DiffusionCode1
Sequential transport maps using SoS density estimation and α-divergencesCode0
Demonstration of Robust and Efficient Quantum Property Learning with Shallow ShadowsCode2
Stochastic Approximation with Biased MCMC for Expectation MaximizationCode0
Quasi-Bayesian Estimation and Inference with Control Functions—0
Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification—0
Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse PlanningCode1
Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization—0
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Benchmark Results

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