SOTAVerified

Bayesian Inference

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

Papers

Showing 17511775 of 2226 papers

TitleStatusHype
A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Process0
Accelerated physical emulation of Bayesian inference in spiking neural networks0
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)Code1
Understanding and Accelerating Particle-Based Variational InferenceCode1
Scalable approximate Bayesian inference for particle tracking dataCode0
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)0
Rating Distributions and Bayesian Inference: Enhancing Cognitive Models of Spatial Language Use0
An Introduction to Animal Movement Modeling with Hidden Markov Models using Stan for Bayesian Inference0
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology0
Random Feature Stein DiscrepanciesCode0
Large-Scale Stochastic Sampling from the Probability SimplexCode0
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning0
Uncertainty Estimations by Softplus normalization in Bayesian Convolutional Neural Networks with Variational InferenceCode0
Reconstructing networks with unknown and heterogeneous errors0
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-DivergencesCode0
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference0
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing0
Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filterCode0
Efficient Bayesian Inference for a Gaussian Process Density Model0
Wasserstein Variational Inference0
Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Exploration in Reinforcement LearningCode0
Semi-Implicit Variational InferenceCode0
Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic ProgrammingCode0
Likelihood-free inference with emulator networksCode0
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers0
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Benchmark Results

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