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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
Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning—0
Mean-field theory of graph neural networks in graph partitioning—0
Towards Principled Uncertainty Estimation for Deep Neural Networks—0
Learning and Inference in Hilbert Space with Quantum Graphical Models—0
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach—0
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE)—0
Stochastic Gradient MCMC for State Space ModelsCode0
Good Initializations of Variational Bayes for Deep Models—0
EMHMM Simulation Study—0
The Deep Weight PriorCode0
Metropolis-Hastings view on variational inference and adversarial training—0
Bayesian Inference of Self-intention Attributed by Observer—0
Variational Bayesian Monte CarloCode1
Uncertainty in Neural Networks: Approximately Bayesian EnsemblingCode0
Dropout as a Structured Shrinkage PriorCode0
An easy-to-use empirical likelihood ABC method—0
Sketching for Latent Dirichlet-Categorical Models—0
Uncertainty-aware generative models for inferring document class prevalenceCode0
Bayesian Prediction of Future Street Scenes using Synthetic LikelihoodsCode0
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers—0
Adaptive Gaussian process surrogates for Bayesian inference—0
Bayesian inference for PCA and MUSIC algorithms with unknown number of sourcesCode0
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach—0
Flexible Mixture Modeling on Constrained Spaces—0
Stochasticity from function -- why the Bayesian brain may need no noise—0
Simulator Calibration under Covariate Shift with Kernels—0
Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data—0
Predictive Collective Variable Discovery with Deep Bayesian ModelsCode0
Robustness Guarantees for Bayesian Inference with Gaussian ProcessesCode0
A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM—0
Seeing Tree Structure from Vibration—0
Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting—0
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion—0
Differentially Private Bayesian Inference for Exponential FamiliesCode0
Semantic Information G Theory and Logical Bayesian Inference for Machine Learning—0
A Novel Deterministic Framework for Non-probabilistic Recommender SystemsCode0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM—0
Cortical Microcircuits from a Generative Vision Model—0
Winner-Take-All as Basic Probabilistic Inference Unit of Neuronal Circuits—0
Efficient Bayesian Inference of Sigmoidal Gaussian Cox ProcessesCode0
Sprucing up the trees -- Error detection in treebanks—0
Towards identifying the optimal datasize for lexically-based Bayesian inference of linguistic phylogenies—0
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability—0
Automatic Bayesian Density Analysis—0
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard ModelCode0
Online Label Aggregation: A Variational Bayesian Approach—0
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methodsCode0
Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors—0
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex ModelsCode0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
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Benchmark Results

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