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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 1701–1750 of 2226 papers

TitleStatusHype
Data Subsampling for Bayesian Neural NetworksCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Debiased Bayesian inference for average treatment effectsCode0
deBInfer: Bayesian inference for dynamical models of biological systems in RCode0
Predictive, scalable and interpretable knowledge tracing on structured domainsCode0
The Deep Weight PriorCode0
Learning Bayesian posteriors with neural networks for gravitational-wave inferenceCode0
Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomyCode0
A Novel Deterministic Framework for Non-probabilistic Recommender SystemsCode0
Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biologyCode0
Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal LayersCode0
Learning Differentiable Particle Filter on the FlyCode0
Bayesian Conditional Density FilteringCode0
Deep Active Inference as Variational Policy GradientsCode0
Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood EstimationCode0
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data CorruptionsCode0
Deep Bayesian inference for seismic imaging with tasksCode0
Deep Bayesian Structure NetworksCode0
Data-driven Approach for Interpolation of Sparse DataCode0
Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform InversionCode0
Bayesian causal discovery from unknown general interventionsCode0
Bayesian Online Natural Gradient (BONG)Code0
Accelerated Information Gradient flowCode0
CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional DataCode0
Simultaneous identification of models and parameters of scientific simulatorsCode0
Learning of Weighted Multi-layer Networks via Dynamic Social Spaces, with Application to Financial Interbank TransactionsCode0
The Exact Asymptotic Form of Bayesian Generalization Error in Latent Dirichlet AllocationCode0
Deep Learning and genetic algorithms for cosmological Bayesian inference speed-upCode0
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in KenyaCode0
Efficient Gradient Flows in Sliced-Wasserstein SpaceCode0
Variational Inference with Continuously-Indexed Normalizing FlowsCode0
Learning Summary Statistics for Bayesian Inference with AutoencodersCode0
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
Deep Neural Networks as Gaussian ProcessesCode0
SNAPE-PM: Building and Utilizing Dynamic Partner Models for Adaptive Explanation GenerationCode0
Bayesian Online Prediction of Change PointsCode0
Undirected Graphical Models as Approximate PosteriorsCode0
On out-of-distribution detection with Bayesian neural networksCode0
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systemsCode0
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active InferenceCode0
COVID-19 detection using chest X-rays: is lung segmentation important for generalization?Code0
Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian InferenceCode0
SoftCVI: Contrastive variational inference with self-generated soft labelsCode0
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma AugmentationCode0
SoftDropConnect (SDC) -- Effective and Efficient Quantification of the Network Uncertainty in Deep MR Image AnalysisCode0
Leveraging Joint Predictive Embedding and Bayesian Inference in Graph Self Supervised LearningCode0
Leveraging joint sparsity in hierarchical Bayesian learningCode0
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian InferenceCode0
Detecting structural perturbations from time series with deep learningCode0
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learningCode0
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Benchmark Results

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