SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1050 of 2226 papers

TitleStatusHype
Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?—0
Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC—0
Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization—0
Flexible Bayesian Inference on Partially Observed Epidemics—0
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach—0
Flexible Mixture Modeling on Constrained Spaces—0
Divide, Conquer, Combine Bayesian Decision Tree Sampling—0
Bayesian Inference for Gamma Models—0
Forecasting Macroeconomic Dynamics using a Calibrated Data-Driven Agent-based Model—0
Forecasting using incomplete models—0
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation—0
Distribution-Level AirComp for Wireless Federated Learning under Data Scarcity and Heterogeneity—0
Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning—0
Formalizing Preference Utilitarianism in Physical World Models—0
Forming Real-World Human-Robot Cooperation for Tasks With General Goal—0
Bayesian inference for dynamic spatial quantile models with interactive effects—0
Foundation Models for Causal Inference via Prior-Data Fitted Networks—0
Free energy and inference in living systems—0
Free Energy Minimization: A Unified Framework for Modelling, Inference, Learning,and Optimization—0
Frequentist Guarantees of Distributed (Non)-Bayesian Inference—0
Semantic Information G Theory and Logical Bayesian Inference for Machine Learning—0
From Shannon's Channel to Semantic Channel via New Bayes' Formulas for Machine Learning—0
Distribution learning via neural differential equations: minimal energy regularization and approximation theory—0
Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
Distributed Variational Bayesian Algorithms Over Sensor Networks—0
A Novel Gaussian Process Based Ground Segmentation Algorithm with Local-Smoothness Estimation—0
A deep learning framework for geodesics under spherical Wasserstein-Fisher-Rao metric and its application for weighted sample generation—0
Accelerating a hybrid continuum-atomistic fluidic model with on-the-fly machine learning—0
Distributed Bayesian Inference for Large-Scale IoT Systems—0
Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks—0
Bayesian inference for bivariate ranks—0
Bayesian Inference by Symbolic Model Checking—0
Distilling Calibration via Conformalized Credal Inference—0
Bayesian inference as iterated random functions with applications to sequential inference in graphical models—0
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting—0
Bayesian inference as a cross-linguistic word segmentation strategy: Always learning useful things—0
A normative theory of social conflict—0
A Deep Learning Approach to Dst Index Prediction—0
Discriminative Relational Topic Models—0
Bayesian inference and superstatistics to describe long memory processes of financial time series—0
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation—0
Bayesian inference and role of astrocytes in amyloid-beta dynamics with modelling of Alzheimer's disease using clinical data—0
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics—0
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits—0
Dirichlet Bayesian Network Scores and the Maximum Relative Entropy Principle—0
Dimension reduction via score ratio matching—0
Bayesian inference and neural estimation of acoustic wave propagation—0
A Nonparametric Bayesian Approach to Uncovering Rat Hippocampal Population Codes During Spatial Navigation—0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
Show:102550
← PrevPage 21 of 45Next →

Benchmark Results

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