Sequential Bayesian Inference

Description from the archive archive 2025-07-28.

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Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (20 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Particle Flow Bayes' Rule
  2 Feb 2019 2 repositories listed Syntology ran 1 of 8 samples · 7 unverified
  We present a particle flow realization of Bayes' rule, where an ODE-based neural operator is used to transport particles from a prior to its posterior after a new observation.
• Bayesian Online Natural Gradient (BONG)
  30 May 2024 1 repository listed Syntology ran 8 of 9 samples · 1 unverified
  We propose a novel approach to sequential Bayesian inference based on variational Bayes (VB).
• Continual Learning via Sequential Function-Space Variational Inference
  28 Dec 2023 1 repository listed Syntology ran 8 of 12 samples · 4 unverified
  Sequential Bayesian inference over predictive functions is a natural framework for continual learning from streams of data.
• Learning Differentiable Particle Filter on the Fly
  10 Dec 2023 1 repository listed
  Differentiable particle filters are an emerging class of sequential Bayesian inference techniques that use neural networks to construct components in state space models.
• A digital twin framework for civil engineering structures
  2 Aug 2023 1 repository listed
  This work proposes a predictive digital twin approach to the health monitoring, maintenance, and management planning of civil engineering structures.
• On Sequential Bayesian Inference for Continual Learning
  4 Jan 2023 1 repository listed
  Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks.
• Discriminative Bayesian filtering lends momentum to the stochastic Newton method for minimizing log-convex functions
  27 Apr 2021 1 repository listed
  To minimize the average of a set of log-convex functions, the stochastic Newton method iteratively updates its estimate using subsampled versions of the full objective's gradient and Hessian.
• The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models
  1 May 2020 1 repository listed
  Extensions to the Kalman filter, including the extended and unscented Kalman filters, incorporate linearizations for models where the observation model p(observation∣state) is nonlinear.
• Functional Regularisation for Continual Learning with Gaussian Processes
  31 Jan 2019 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  We introduce a framework for Continual Learning (CL) based on Bayesian inference over the function space rather than the parameters of a deep neural network.
• A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding
  17 Jul 2018 1 repository listed
  Given a stationary state-space model that relates a sequence of hidden states and corresponding measurements or observations, Bayesian filtering provides a principled statistical framework for inferring the posterior…
• Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter
  29 May 2018 1 repository listed
  In this work, a novel sequential Monte Carlo filter is introduced which aims at efficient sampling of high-dimensional state spaces with a limited number of particles.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.