SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Showing 251300 of 2226 papers

TitleStatusHype
Approximate Variational Inference Based on a Finite Sample of Gaussian Latent VariablesCode0
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian InferenceCode0
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at ScaleCode0
Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI CapabilitiesCode0
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep NetworksCode0
Data-driven Modeling and Inference for Bayesian Gaussian Process ODEs via Double Normalizing FlowsCode0
Adversarial α-divergence Minimization for Bayesian Approximate InferenceCode0
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-DivergencesCode0
Do Bayesian Variational Autoencoders Know What They Don't Know?Code0
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over SimplexCode0
DPER: Dynamic Programming for Exist-Random Stochastic SATCode0
Exploring helical dynamos with machine learningCode0
Approximate Bayesian Neural Doppler ImagingCode0
Distilling Importance Sampling for Likelihood Free InferenceCode0
Distilling Model KnowledgeCode0
AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithmsCode0
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon SynapseCode0
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian InferenceCode0
Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous DataCode0
A Bayesian Method for Joint Clustering of Vectorial Data and Network DataCode0
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of MultipliersCode0
Differentially Private Bayesian Learning on Distributed DataCode0
Accelerating Convergence of Stein Variational Gradient Descent via Deep UnfoldingCode0
Differentially Private Distributed Bayesian Linear Regression with MCMCCode0
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning AlgorithmsCode0
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence ClusteringCode0
Differentially Private Bayesian Inference for Exponential FamiliesCode0
Differentially Private Federated Variational InferenceCode0
A digital twin framework for civil engineering structuresCode0
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma AugmentationCode0
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active InferenceCode0
Detecting structural perturbations from time series with deep learningCode0
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-RiskCode0
Deep Learning and genetic algorithms for cosmological Bayesian inference speed-upCode0
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband ItemsCode0
Deep Bayesian Structure NetworksCode0
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in KenyaCode0
A Novel Deterministic Framework for Non-probabilistic Recommender SystemsCode0
deBInfer: Bayesian inference for dynamical models of biological systems in RCode0
Deep Active Inference as Variational Policy GradientsCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Accelerated Stein Variational Gradient FlowCode0
Debiased Bayesian inference for average treatment effectsCode0
Deep Bayesian inference for seismic imaging with tasksCode0
Deep Neural Networks as Gaussian ProcessesCode0
Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform InversionCode0
Accelerated Information Gradient flowCode0
Data-driven Approach for Interpolation of Sparse DataCode0
COVID-19 detection using chest X-rays: is lung segmentation important for generalization?Code0
Greedy inference with structure-exploiting lazy mapsCode0
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Benchmark Results

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