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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 1401–1450 of 2226 papers

TitleStatusHype
Fast Convergence for Langevin with Matrix Manifold Structure—0
Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations—0
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksCode1
Generalized Bayesian Filtering via Sequential Monte Carlo—0
Safe Imitation Learning via Fast Bayesian Reward Inference from PreferencesCode1
πVAE: a stochastic process prior for Bayesian deep learning with MCMCCode1
Sequential Cooperative Bayesian Inference—0
Fast Convergence for Langevin Diffusion with Manifold Structure—0
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization—0
Domain Adaptation as a Problem of Inference on Graphical ModelsCode1
Projected Stein Variational Gradient DescentCode1
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks—0
Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications—0
Value of Information Analysis via Active Learning and Knowledge Sharing in Error-Controlled Adaptive Kriging—0
How Good is the Bayes Posterior in Deep Neural Networks Really?—0
Variational Item Response Theory: Fast, Accurate, and ExpressiveCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with Bayesian inference for uncertainty-based quality-control—0
Transport Gaussian Processes for Regression—0
The Case for Bayesian Deep Learning—0
Bayesian Reasoning with Trained Neural Networks—0
Heterogeneous Learning from Demonstration—0
Well-Calibrated Regression Uncertainty in Medical Imaging with Deep LearningCode1
The Reciprocal Bayesian LASSOCode0
A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting—0
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