{
  "abstract": "Particle filters are a standard tool for nonlinear state estimation, but their resampling step is discrete, preventing gradient-based learning in variational sequential Monte Carlo. We introduce Differentiable Systematic Resampling (DSR), a temperature-controlled relaxation of systematic resampling, that preserves the CDF-ordered, banded structure of systematic resampling while enabling full gradient flow. DSR converges to exact systematic resampling as the temperature vanishes, and we prove a pointwise exponential convergence rate for the induced bias. Compared to optimal-transport-based differentiable resampling, DSR avoids iterative solvers and has substantially lower computational overhead. Experiments on stochastic dynamical systems and real-world handwriting data show that DSR achieves comparable or superior filtering and dynamics learning performance.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.12094",
  "author_total": 2,
  "authors": [
    {
      "name": "Fredrik Cumlin"
    },
    {
      "name": "Saikat Chatterjee"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7sjjxzxz4bmn8.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.12094",
  "fulltext_url": null,
  "id": "7sjjxzxz4bmn8",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.12094",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "eess.SP"
    ],
    [
      "arxiv",
      "stat.ML"
    ],
    [
      "openalex",
      "1702|Target Tracking and Data Fusion in Sensor Networks"
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  ],
  "openalex": "W7221085638",
  "pdf_url": "https://arxiv.org/pdf/2610.12094",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7sjjxzxz4bmn8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:36:41Z",
      "native_id": "2610.12094",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.12094"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ML",
      "subfield": "statistics"
    }
  ],
  "title": "Differentiable Systematic Resampling for Variational Sequential Monte Carlo",
  "title_text": "Differentiable Systematic Resampling for Variational Sequential Monte Carlo",
  "type": "preprint",
  "updated_at": "2026-11-01T12:21:00Z",
  "url": "https://research.draconitic.com/paper/7sjjxzxz4bmn8",
  "venue": "arXiv",
  "versions": []
}