SOTAVerified

Bayesian Inference

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

Papers

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Showing 1826–1850 of 2226 papers

TitleStatusHype
Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family—0
Bayesian inference via rejection filtering—0
Bayesian Inference with Deep Weakly Nonlinear Networks—0
Bayesian inference with finitely wide neural networks—0
Bayesian Inference with Generative Adversarial Network Priors—0
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning—0
Bayesian Inference with Posterior Regularization and applications to Infinite Latent SVMs—0
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition—0
Bayesian Interpolation with Deep Linear Networks—0
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration—0
BInGo: Bayesian Intrinsic Groupwise Registration via Explicit Hierarchical Disentanglement—0
Bayesian Invariant Risk Minimization—0
Bayesian Inverse Contextual Reasoning for Heterogeneous Semantics-Native Communication—0
Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise—0
Bayesian Knowledge-driven Critiquing with Indirect Evidence—0
Bayesian Learning for Neural Networks: an algorithmic survey—0
Bayesian Learning of Kernel Embeddings—0
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes—0
Bayesian Learning via Neural Schrödinger-Föllmer Flows—0
Bayesian Logistic Shape Model Inference: application to cochlea image segmentation—0
Bayesian Low-Rank Interpolative Decomposition for Complex Datasets—0
Bayesian Low Rank Tensor Ring Model for Image Completion—0
Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias—0
Bayesian mechanics of self-organising systems—0
Bayesian Metaplasticity from Synaptic Uncertainty—0
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Benchmark Results

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