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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 951–1000 of 2226 papers

TitleStatusHype
Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations—0
On the safe use of prior densities for Bayesian model selection—0
PAVI: Plate-Amortized Variational Inference—0
BInGo: Bayesian Intrinsic Groupwise Registration via Explicit Hierarchical Disentanglement—0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference—0
A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees—0
Functional Ensemble DistillationCode0
Information Threshold, Bayesian Inference and Decision-Making—0
Excess risk analysis for epistemic uncertainty with application to variational inference—0
Bayesian Inference of Stochastic Dynamical Networks—0
Bayesian Inference for the Multinomial Probit Model under Gaussian Prior Distribution—0
Robust Anytime Learning of Markov Decision ProcessesCode0
Bayesian Low-Rank Interpolative Decomposition for Complex Datasets—0
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning—0
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference—0
Consistent and fast inference in compartmental models of epidemics using Poisson Approximate LikelihoodsCode0
Optimal Neural Network Approximation of Wasserstein Gradient Direction via Convex OptimizationCode0
Analytics of Business Time Series Using Machine Learning and Bayesian Inference—0
Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQLCode0
Emergent Communication through Metropolis-Hastings Naming Game with Deep Generative ModelsCode0
Extended molt phenology models improve inferences about molt duration and timingCode0
Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization—0
RL with KL penalties is better viewed as Bayesian inference—0
Quasi Black-Box Variational Inference with Natural Gradients for Bayesian Learning—0
Parameters identification for an inverse problem arising from a binary option using a Bayesian inference approach—0
Variational Inference for Bayesian Bridge Regression—0
DPER: Dynamic Programming for Exist-Random Stochastic SATCode0
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling—0
Nonblind image deconvolution via leveraging model uncertainty in an untrained deep neural networkCode0
DPO: Dynamic-Programming Optimization on Hybrid ConstraintsCode0
Intuitive and Efficient Human-robot Collaboration via Real-time Approximate Bayesian Inference—0
On the Convergence of the Shapley Value in Parametric Bayesian Learning GamesCode0
Addressing Census data problems in race imputation via fully Bayesian Improved Surname Geocoding and name supplements—0
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems—0
Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking—0
Sequential Importance Sampling for Hybrid Model Bayesian Inference to Support Bioprocess Mechanism Learning and Robust Control—0
A Deep Learning Approach to Dst Index Prediction—0
Bézier Curve Gaussian Processes—0
A Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction—0
TopWORDS-Seg: Simultaneous Text Segmentation and Word Discovery for Open-Domain Chinese Texts via Bayesian Inference—0
Approximating Permutations with Neural Network Components for Travelling Photographer Problem—0
Deep Ensemble as a Gaussian Process Approximate Posterior—0
Statistical applications of contrastive learning—0
Designing Perceptual Puzzles by Differentiating Probabilistic Programs—0
A Bayesian Approach To Graph Partitioning—0
A majorization-minimization algorithm for nonnegative binary matrix factorization—0
A stochastic Stein Variational Newton methodCode0
Beta Residuals: Improving Fault-Tolerant Control for Sensory Faults via Bayesian Inference and Precision Learning—0
Learning-based Bounded Synthesis for Semi-MDPs with LTL Specifications—0
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Benchmark Results

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