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