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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 576–600 of 2226 papers

TitleStatusHype
Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging—0
Robust Bayesian Inference for Berkson and Classical Measurement Error Models—0
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive AdvantagesCode0
Metropolis-Hastings algorithm in joint-attention naming game: Experimental semiotics study—0
On Mixing Rates for Bayesian CART—0
Low-rank extended Kalman filtering for online learning of neural networks from streaming dataCode1
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in KenyaCode0
Recursive Metropolis-Hastings Naming Game: Symbol Emergence in a Multi-agent System based on Probabilistic Generative Models—0
Sparse species interactions reproduce abundance correlation patterns in microbial communities—0
Parallelized Acquisition for Active Learning using Monte Carlo SamplingCode1
A Bayesian sparse factor model with adaptive posterior concentration—0
Conditional score-based diffusion models for Bayesian inference in infinite dimensionsCode1
Bayesian inference and neural estimation of acoustic wave propagation—0
Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming ApproachCode1
Improving Neural Additive Models with Bayesian PrinciplesCode0
Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks—0
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty—0
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo AlgorithmsCode0
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation—0
On the Convergence of Black-Box Variational Inference—0
Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic LikelihoodCode0
Bayesian calibration of differentiable agent-based models—0
Simultaneous identification of models and parameters of scientific simulatorsCode0
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior InferenceCode0
Adversarial robustness of amortized Bayesian inferenceCode0
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Benchmark Results

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