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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 1201–1250 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
Score Matched Neural Exponential Families for Likelihood-Free InferenceCode1
Forming Real-World Human-Robot Cooperation for Tasks With General Goal—0
Spacecraft Collision Risk Assessment with Probabilistic ProgrammingCode1
Lévy walks derived from a Bayesian decision-making model in non-stationary environments—0
Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interactionCode0
Bayesian Neural Ordinary Differential Equations—0
Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian InferenceCode0
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent—0
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantificationCode1
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty RegularizationCode0
Bayesian PseudocoresetsCode0
Online Bayesian Goal Inference for Boundedly Rational Planning Agents—0
Generalised Bayesian Filtering via Sequential Monte Carlo—0
Bidirectional Convolutional Poisson Gamma Dynamical SystemsCode0
Baxter Permutation ProcessCode0
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks—0
Towards constraining warm dark matter with stellar streams through neural simulation-based inferenceCode1
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious timeCode1
Distributed Variational Bayesian Algorithms Over Sensor Networks—0
Free Energy Minimization: A Unified Framework for Modelling, Inference, Learning,and Optimization—0
Parametric Bootstrap Ensembles as Variational Inference—0
On the Inconsistency of Bayesian Inference for Misspecified Neural Networks—0
Gaussian Density Parametrization Flow: Particle and Stochastic Approaches—0
Variational Refinement for Importance SamplingUsing the Forward Kullback-Leibler Divergence—0
Transforming Worlds: Automated Involutive MCMC for Open-Universe Probabilistic Models—0
Enriching ImageNet with Human Similarity Judgments and Psychological EmbeddingsCode1
Understanding Variational Inference in Function-SpaceCode0
Generalized Posteriors in Approximate Bayesian ComputationCode0
Stein Variational Model Predictive Control—0
On a Variational Approximation based Empirical Likelihood ABC Method—0
Efficient and Transferable Adversarial Examples from Bayesian Neural NetworksCode0
Extending the statistical software package Engine for Likelihood-Free Inference—0
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation—0
Transforming Gaussian Processes With Normalizing FlowsCode1
Problems using deep generative models for probabilistic audio source separation—0
Differentially Private Bayesian Inference for Generalized Linear Models—0
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo—0
Bayesian Deep Learning via Subnetwork InferenceCode1
Micro-CT Synthesis and Inner Ear Super Resolution via Generative Adversarial Networks and Bayesian Inference—0
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance—0
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Benchmark Results

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