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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 1076–1100 of 2226 papers

TitleStatusHype
Repulsive Deep Ensembles are BayesianCode1
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization—0
Variational multiple shooting for Bayesian ODEs with Gaussian processesCode1
Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous DataCode0
Out-of-Distribution Detection Using Union of 1-Dimensional SubspacesCode1
Being a Bit Frequentist Improves Bayesian Neural NetworksCode0
Goal-Directed Planning by Reinforcement Learning and Active Inference—0
Quasi-Bayesian Dual Instrumental Variable RegressionCode0
Variational Causal Networks: Approximate Bayesian Inference over Causal StructuresCode1
Deep Bayesian Unsupervised Lifelong LearningCode1
Analog Seizure Detection for Implanted Responsive Neurostimulation—0
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs—0
Quantum Speedup of Natural Gradient for Variational Bayes—0
An Interpretable Neural Network for Parameter Inference—0
Data augmentation in Bayesian neural networks and the cold posterior effect—0
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random FeaturesCode0
RNN with Particle Flow for Probabilistic Spatio-temporal ForecastingCode1
Bayesian Boosting for Linear Mixed Models—0
Nonlinear Hawkes Processes in Time-Varying System—0
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference—0
Antipodes of Label Differential Privacy: PATE and ALIBICode1
Knowing when we do not know: Bayesian continual learning for sensing-based analysis tasks—0
Context-tree weighting for real-valued time series: Bayesian inference with hierarchical mixture models—0
Canonical Cortical Circuits and the Duality of Bayesian Inference and Optimal Control—0
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Benchmark Results

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