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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 1476–1500 of 2226 papers

TitleStatusHype
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning—0
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models—0
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric UncertaintyCode0
Variational Predictive Information Bottleneck—0
Safe-Bayesian Generalized Linear Regression—0
Why bigger is not always better: on finite and infinite neural networks—0
Efficient Bayesian Inference for Nested Simulators—0
Graph Tracking in Dynamic Probabilistic Programs via Source Transformations—0
Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes—0
Bijectors.jl: Flexible transformations for probability distributionsCode0
Neural Permutation Processes—0
Gaussian Process Meta-Representations For Hierarchical Neural Network Weight Priors—0
Bayesian Model Selection for Identifying Markov Equivalent Causal Graphs—0
Stein Variational Gradient Descent for Approximate Bayesian Computation—0
Variationally Inferred Sampling Through a Refined BoundCode0
Interpretable User Models via Decision-rule Gaussian Processes: Preliminary Results on Energy Storage—0
Exchangeable Variational Autoencoders with Applications to Genomic Data—0
AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithmsCode0
Challenges in Markov chain Monte Carlo for Bayesian neural networksCode0
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition—0
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte CarloCode1
Variational Tracking and Prediction with Generative Disentangled State-Space Models—0
Bayesian Meta-Learning for the Few-Shot Setting via Deep KernelsCode1
Validated Variational Inference via Practical Posterior Error BoundsCode1
Distilling Importance Sampling for Likelihood Free InferenceCode0
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Benchmark Results

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