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Sequential Bayesian Inference

Also known as Bayesian filtering or recursive Bayesian estimation, this task aims to perform inference on latent state-space models.

Papers

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Showing 1–20 of 20 papers

TitleStatusHype
Surprise Calibration for Better In-Context Learning—0
Connections between sequential Bayesian inference and evolutionary dynamics—0
Bayesian Online Natural Gradient (BONG)Code0
Continual Learning via Sequential Function-Space Variational InferenceCode1
Learning Differentiable Particle Filter on the FlyCode0
A transport approach to sequential simulation-based inference—0
A digital twin framework for civil engineering structuresCode0
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference—0
On Sequential Bayesian Inference for Continual LearningCode0
Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formation—0
Can Sequential Bayesian Inference Solve Continual Learning?—0
Discriminative Bayesian filtering lends momentum to the stochastic Newton method for minimizing log-convex functionsCode0
The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation ModelsCode1
Hidden Markov Model: Tutorial—0
Thompson Sampling on Symmetric α-Stable Bandits—0
Particle Flow Bayes' RuleCode1
Functional Regularisation for Continual Learning with Gaussian ProcessesCode0
A Discriminative Approach to Bayesian Filtering with Applications to Human Neural DecodingCode0
Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filterCode0
Efficient Low-Order Approximation of First-Passage Time Distributions—0
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