mlsanityData to 7 Oct 2026

DnD Filter: Differentiable State Estimation for Dynamic Systems using Diffusion Models

arXiv 2503.01274 ↗First posted 3 Mar 2025cs.ROcited by 1

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

This paper proposes the DnD Filter, a differentiable filter that utilizes diffusion models for state estimation of dynamic systems. Unlike conventional differentiable filters, which often impose restrictive assumptions on process noise (e.g., Gaussianity), DnD Filter enables a nonlinear state update without such constraints by conditioning a diffusion model on both the predicted state and observational data, capitalizing on its ability to approximate complex distributions. We validate its effectiveness on both a simulated task and a real-world visual odometry task, where DnD Filter consistently outperforms existing baselines. Specifically, it achieves a 25% improvement in estimation accuracy on the visual odometry task compared to state-of-the-art differentiable filters, and even surpasses differentiable smoothers that utilize future measurements. To the best of our knowledge, DnD Filter represents the first successful attempt to leverage diffusion models for state estimation, offering a flexible and powerful framework for nonlinear estimation under noisy measurements.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 28 of its 45 references that are in the map. First posted on arXiv 3 Mar 2025.

Builds on

28 of 45 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting28 Jan

Other references · 27

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  3. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,730
  4. 2015Scheduled Sampling for Sequence Prediction with Recurrent Neural Networkscited by 779
  5. 2022Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learningcited by 543
  6. 2022Is Conditional Generative Modeling all you need for Decision-Making?cited by 504
  7. 2020Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Userscited by 336
  8. 2023NoMaD: Goal Masked Diffusion Policies for Navigation and Explorationcited by 234
  9. 2023ViNT: A Foundation Model for Visual Navigationcited by 210
  10. 2023Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Modelscited by 155
  11. 2023AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Plannerscited by 147
  12. 2023Diffusion Models for Reinforcement Learning: A Surveycited by 84
15 more
  1. 2021Differentiable Particle Filtering via Entropy-Regularized Optimal Transportcited by 59
  2. 2018Differentiable Particle Filters: End-to-End Learning with Algorithmic Priorscited by 58
  3. 2024Tutorial on Diffusion Models for Imaging and Visioncited by 49
  4. 2016Backprop KF: Learning Discriminative Deterministic State Estimatorscited by 47
  5. 2024DiffuserLite: Towards Real-time Diffusion Planningcited by 40
  6. 2023AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Modelcited by 37
  7. 2020Multimodal Sensor Fusion with Differentiable Filterscited by 29
  8. 2020How to Train Your Differentiable Filtercited by 23
  9. 2019DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPscited by 21
  10. 2021Differentiable Factor Graph Optimization for Learning Smootherscited by 17
  11. 2021Differentiable Particle Filters through Conditional Normalizing Flowcited by 15
  12. 2021Interpreting Contact Interactions to Overcome Failure in Robot Assembly Taskscited by 9
  13. 2024DroneDiffusion: Robust Quadrotor Dynamics Learning with Diffusion Modelscited by 6
  14. 2023Enhancing State Estimation in Robots: A Data-Driven Approach with Differentiable Ensemble Kalman Filterscited by 4
  15. 2023Differentiable Bootstrap Particle Filters for Regime-Switching Modelscited by 2

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025DiffPF: Differentiable Particle Filtering with Generative Sampling via Conditional Diffusion Modelscited by 2

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