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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 1301–1350 of 2226 papers

TitleStatusHype
Generalized Posteriors in Approximate Bayesian ComputationCode0
Stein Variational Model Predictive Control—0
On a Variational Approximation based Empirical Likelihood ABC Method—0
Efficient and Transferable Adversarial Examples from Bayesian Neural NetworksCode0
Extending the statistical software package Engine for Likelihood-Free Inference—0
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation—0
Problems using deep generative models for probabilistic audio source separation—0
Differentially Private Bayesian Inference for Generalized Linear Models—0
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo—0
Micro-CT Synthesis and Inner Ear Super Resolution via Generative Adversarial Networks and Bayesian Inference—0
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance—0
Black-box density function estimation using recursive partitioningCode0
Bayesian Importance of Features (BIF)Code0
Bayesian Inference in Physics-Driven Problems with Adversarial Priors—0
From the Expectation Maximisation Algorithm to Autoencoded Variational Bayes—0
Spike and slab variational Bayes for high dimensional logistic regression—0
Analysis of Markov Jump Processes under Terminal ConstraintsCode0
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference—0
Bayesian Inference for Optimal Transport with Stochastic Cost—0
Quantification of Ebola virus replication kinetics in vitro—0
Sequential Likelihood-Free Inference with Neural ProposalCode0
Fundamental Linear Algebra Problem of Gaussian Inference—0
Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging—0
Learning Not to Learn: Nature versus Nurture in Silico—0
Physics-constrained Bayesian inference of state functions in classical density-functional theory—0
Learning Manifold Implicitly via Explicit Heat-Kernel Learning—0
Bayesian Policy Search for Stochastic Domains—0
Towards Scalable Bayesian Learning of Causal DAGs—0
Amortized Conditional Normalized Maximum Likelihood—0
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference—0
Multilevel Gibbs Sampling for Bayesian Regression—0
On the representation and learning of monotone triangular transport mapsCode0
Partially Observable Online Change Detection via Smooth-Sparse Decomposition—0
Remote sensing image fusion based on Bayesian GAN—0
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference—0
Epidemic mitigation by statistical inference from contact tracing data—0
Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modelingCode0
Optimality of short-term synaptic plasticity in modelling certain dynamic environments—0
Density Estimation via Bayesian Inference Engines—0
Tracking disease outbreaks from sparse data with Bayesian inference—0
Non-linear fitting with joint spatial regularization in Arterial Spin Labeling—0
Towards Flexible Sparsity-Aware Modeling: Automatic Tensor Rank Learning Using The Generalized Hyperbolic Prior—0
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution SettingsCode0
Bayesian Perceptron: Towards fully Bayesian Neural Networks—0
β-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of OutliersCode0
The linear conditional expectation in Hilbert space—0
Surrogate Model For Field Optimization Using Beta-VAE Based Regression—0
Blindness of score-based methods to isolated components and mixing proportions—0
Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles—0
Bayesian geoacoustic inversion using mixture density network—0
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Benchmark Results

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