{
  "id": 6369516,
  "title": "Recovering Weak Signals with Normalizing Flows",
  "url": "https://urgent.news/2026/09/06/recovering-weak-signals-with-normalizing-flows",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-06T04:44:34.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.06382v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "In many scientific disciplines, weak signals of interest are obscured by dominant nuisance signals that are several orders of magnitude stronger. Recovering these weak signals requires subtracting the dominant ones; however, this calibration process inherently distorts or partially suppresses the underlying signal of interest. To address this problem, we propose the use of normalizing flow models…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}