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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 1251–1275 of 2226 papers

TitleStatusHype
Weighted Mean Curvature—0
What does the free energy principle tell us about the brain?—0
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution—0
Why bigger is not always better: on finite and infinite neural networks—0
Winner-Take-All as Basic Probabilistic Inference Unit of Neuronal Circuits—0
Worst-Case Analysis is Maximum-A-Posteriori Estimation—0
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors—0
Decentralized Bayesian Learning over Graphs—0
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo—0
Bottom-up data integration in polymer models of chromatin organisation—0
Bridging Privacy and Robustness for Trustworthy Machine Learning—0
Decipherment Complexity in 1:1 Substitution Ciphers—0
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control—0
Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
Declarative Modeling and Bayesian Inference of Dark Matter Halos—0
Decoupled Variational Gaussian Inference—0
Deep Active Inference for Autonomous Robot Navigation—0
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference—0
Deep de Finetti: Recovering Topic Distributions from Large Language Models—0
Deep Ensemble as a Gaussian Process Approximate Posterior—0
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging—0
Deep importance sampling using tensor trains with application to a priori and a posteriori rare event estimation—0
Deep Knowledge Tracing with Learning Curves—0
Deep Learning Aided Laplace Based Bayesian Inference for Epidemiological Systems—0
Deep Learning and Bayesian inference for Inverse Problems—0
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Benchmark Results

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