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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 1426–1450 of 2226 papers

TitleStatusHype
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization—0
Analysis of Bayesian Inference Algorithms by the Dynamical Functional Approach—0
Efficient Debiased Evidence Estimation by Multilevel Monte Carlo Sampling—0
A Technical Critique of Some Parts of the Free Energy Principle—0
Probabilistic Reasoning across the Causal Hierarchy—0
Bayesian task embedding for few-shot Bayesian optimizationCode0
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics—0
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference—0
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning—0
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning AlgorithmsCode0
Attention-Aware Answers of the Crowd—0
Blang: Bayesian declarative modelling of general data structures and inference via algorithms based on distribution continuaCode0
Quantile Propagation for Wasserstein-Approximate Gaussian ProcessesCode0
NFAD: Fixing anomaly detection using normalizing flowsCode0
Normalizing Constant Estimation with Gaussianized Bridge SamplingCode0
Diagnosing model misspecification and performing generalized Bayes' updates via probabilistic classifiers—0
On the relationship between multitask neural networks and multitask Gaussian Processes—0
A Closer Look at Disentangling in β-VAE—0
Hidden Markov Model: Tutorial—0
Neural Tangents: Fast and Easy Infinite Neural Networks in PythonCode0
Overcoming Catastrophic Forgetting by Generative Regularization—0
On the geometry of Stein variational gradient descent—0
A Bayesian Inference Framework for Procedural Material Parameter Estimation—0
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High DimensionsCode0
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models—0
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Benchmark Results

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