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 1201–1210 of 2226 papers

TitleStatusHype
Scalable Bayesian Inverse Reinforcement Learning by Auto-Encoding Reward—0
Variational Multi-Task Learning—0
Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational InferenceCode1
A Bayesian-Symbolic Approach to Learning and Reasoning for Intuitive Physics—0
Uncertainty Calibration Error: A New Metric for Multi-Class Classification—0
A Tutorial on Sparse Gaussian Processes and Variational Inference—0
On Batch Normalisation for Approximate Bayesian Inference—0
Gradient-Free Adversarial Attacks for Bayesian Neural NetworksCode0
Alternating linear scheme in a Bayesian framework for low-rank tensor approximation—0
Recent advances in deep learning theory—0
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Benchmark Results

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