SOTAVerified

Bayesian Inference

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

Papers

Showing 18011825 of 2226 papers

TitleStatusHype
Deep Network Regularization via Bayesian Inference of Synaptic Connectivity0
Analysis of Langevin Monte Carlo via convex optimization0
Conditionally Independent Multiresolution Gaussian ProcessesCode0
BRUNO: A Deep Recurrent Model for Exchangeable DataCode0
Variational Autoencoders for Collaborative FilteringCode0
Variational Autoencoders for Collaborative FilteringCode1
A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization0
Improving Quadrature for Constrained IntegrandsCode0
Bayesian inference for bivariate ranks0
Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration0
Weighted Community Detection and Data Clustering Using Message Passing0
A Review of Multiple Try MCMC algorithms for Signal Processing0
A Distributed Framework for the Construction of Transport Maps0
Bayesian reconstruction of HIV transmission trees from viral sequences and uncertain infection times0
Experimentally detecting a quantum change point via Bayesian inference0
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification0
Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections0
Gaussian Process Neurons0
Interpreting Deep Classification Models With Bayesian Inference0
A Scalable Laplace Approximation for Neural NetworksCode0
On Statistical Optimality of Variational Bayes0
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators0
Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise0
Assumed Density Filtering Q-learningCode0
Approximations in the homogeneous Ising model0
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Benchmark Results

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