{
  "id": 13500,
  "url": "https://arxiv.org/abs/2607.21088v1",
  "title": "CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data",
  "summary": "Deep subspace clustering plays a critical role in applications involving multivariate spatiotemporal data, such as sea ice monitoring, disease spread analysis, and tracking neuro-degeneration over time. Despite recent advances, existing methods primarily rely on geometric self-expressiveness, assume static subspace structures, and often fail to capture causal dependencies, local spatial interactions, and long-range temporal dynamics inherent in complex spatiotemporal systems. To address these li",
  "authors": "Francis Ndikum Nji, Vandana Janeja, Jianwu Wang",
  "category": "research",
  "topics": "privacy-surveillance",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-23T09:19:17.000Z",
  "fetched_at": "2026-07-25T05:10:48.796Z",
  "source_slug": "arxiv-cslg",
  "source_name": "arXiv cs.LG",
  "source_homepage": "https://arxiv.org/list/cs.LG/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/13500",
  "original_url": "https://arxiv.org/abs/2607.21088v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}