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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
Prediction Uncertainty Estimation for Hate Speech Classification—0
Predictive Approximate Bayesian Computation via Saddle Points—0
Predictive coding and stochastic resonance as fundamental principles of auditory perception—0
Predictive Coding Networks and Inference Learning: Tutorial and Survey—0
Predictive Coding Theories of Cortical Function—0
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo—0
Predictive Uncertainty Quantification with Compound Density Networks—0
Primitive-based Shape Abstraction via Nonparametric Bayesian Inference—0
Towards Principled Uncertainty Estimation for Deep Neural Networks—0
Priors in Bayesian Deep Learning: A Review—0
PRISM: Probabilistic Real-Time Inference in Spatial World Models—0
Privacy Amplification Via Bernoulli Sampling—0
Probabilistic Block Term Decomposition for the Modelling of Higher-Order Arrays—0
Probabilistic CCA with Implicit Distributions—0
Probabilistic Deep Learning with Generalised Variational Inference—0
Probabilistic Inference for Learning from Untrusted Sources—0
Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation—0
Probabilistic inverse reinforcement learning in unknown environments—0
Probabilistic inverse reinforcement learning in unknown environments—0
Probabilistic Model-Based Approach for Heart Beat Detection—0
Probabilistic Model Checking of Robots Deployed in Extreme Environments—0
Probabilistic model predictive safety certification for learning-based control—0
Probabilistic Object Classification using CNN ML-MAP layers—0
Probabilistic Position-Aided Beam Selection for mmWave MIMO Systems—0
Probabilistic Reasoning across the Causal Hierarchy—0
Probabilistic Regular Tree Priors for Scientific Symbolic Reasoning—0
Synaptic plasticity as Bayesian inference—0
Probabilistic Wind Park Power Prediction using Bayesian Deep Learning and Generative Adversarial Networks—0
PROBE-GK: Predictive Robust Estimation using Generalized Kernels—0
Problems using deep generative models for probabilistic audio source separation—0
Procedure Planning in Instructional Videos via Contextual Modeling and Model-based Policy Learning—0
Programs as Singularities—0
Projecting basis functions with tensor networks for Gaussian process regression—0
Provable Bayesian Inference via Particle Mirror Descent—0
Pruning a neural network using Bayesian inference—0
Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models—0
Pseudo-Marginal Bayesian Inference for Gaussian Processes—0
Pseudo-Marginal Hamiltonian Monte Carlo—0
Quantification of Ebola virus replication kinetics in vitro—0
Quantifying active and resistive stresses in adherent cells—0
Quantifying Aspect Bias in Ordinal Ratings using a Bayesian Approach—0
Quantifying uncertainty with GAN-based priors—0
Quantum Speedup of Natural Gradient for Variational Bayes—0
Quasi-Bayesian Estimation and Inference with Control Functions—0
Quasi Black-Box Variational Inference with Natural Gradients for Bayesian Learning—0
Quick and energy-efficient Bayesian computing of binocular disparity using stochastic digital signals—0
QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision—0
RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models—0
Ranking Policy Learning via Marketplace Expected Value Estimation From Observational Data—0
Rating Distributions and Bayesian Inference: Enhancing Cognitive Models of Spatial Language Use—0
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Benchmark Results

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