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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 1101–1150 of 2226 papers

TitleStatusHype
Locally Differentially Private Bayesian Inference—0
A Scalable Inference Method For Large Dynamic Economic Systems—0
Efficient Gradient Flows in Sliced-Wasserstein SpaceCode0
Bayesian Inference in Physics-Based Nonlinear Flame Models—0
Efficient posterior inference & generalization in physics-based Bayesian inference with conditional GANs—0
An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System—0
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue—0
Godot is not coming: when we will let innovations enter psychiatry?—0
A Bayesian Approach for Medical Inquiry and Disease Inference in Automated Differential DiagnosisCode0
Probing as Quantifying Inductive BiasCode0
On out-of-distribution detection with Bayesian neural networksCode0
Deep Bayesian inference for seismic imaging with tasksCode0
Kernel Interpolation as a Bayes Point MachineCode0
Pathologies in priors and inference for Bayesian transformers—0
De-randomizing MCMC dynamics with the diffusion Stein operator—0
MetaCOG: A Hierarchical Probabilistic Model for Learning Meta-Cognitive Visual RepresentationsCode0
Procedure Planning in Instructional Videos via Contextual Modeling and Model-based Policy Learning—0
Kalman Bayesian Neural Networks for Closed-form Online Learning—0
Arbitrary Marginal Neural Ratio Estimation for Simulation-based InferenceCode0
Semantic Classification and Learning Using a Linear Tranformation Model in a Probabilistic Type Theory with Records—0
On the Implicit Biases of Architecture & Gradient Descent—0
EinSteinVI: General and Integrated Stein Variational Inference—0
Simulation-based Bayesian inference for multi-fingered robotic grasping—0
Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit—0
Contributions to Large Scale Bayesian Inference and Adversarial Machine Learning—0
Uncertainty quantification in covid-19 spread: lockdown effects—0
Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions—0
Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation—0
Asynchronous and Distributed Data Augmentation for Massive Data SettingsCode0
Automatic maneuver detection and tracking of space objects in optical survey scenarios based on stochastic hybrid systems formulation—0
Microbiome subcommunity learning with logistic-tree normal latent Dirichlet allocationCode0
Modeling Massive Spatial Datasets Using a Conjugate Bayesian Linear Regression Framework—0
A theory of representation learning gives a deep generalisation of kernel methods—0
A Mathematical Walkthrough and Discussion of the Free Energy Principle—0
Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive ModelsCode0
Modeling Item Response Theory with Stochastic Variational Inference—0
Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ballCode0
Modeling time evolving COVID-19 uncertainties with density dependent asymptomatic infections and social reinforcement—0
A survey on Bayesian inference for Gaussian mixture model—0
Approximate Bayesian Neural Doppler ImagingCode0
A fast asynchronous MCMC sampler for sparse Bayesian inferenceCode0
Stability and Convergence of Stochastic Particle Flow Filters—0
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs—0
Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling—0
Deep Stable neural networks: large-width asymptotics and convergence rates—0
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning—0
Are Bayesian neural networks intrinsically good at out-of-distribution detection?Code0
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference—0
A Multiple-Instance Learning Approach for the Assessment of Gallbladder Vascularity from Laparoscopic Images—0
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference—0
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Benchmark Results

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