Pith Number

pith:HHEYAQE2

pith:2026:HHEYAQE2W3MV5UW7UJGUJTG3QI

not attested not anchored not stored refs resolved

A Resampling-Based Framework for Network Structure Learning in High-Dimensional Data

Paola Sebastiani, Stefano Monti, Zeyuan Song, Ziwei Huang

RSNet applies resampling to produce reliable network estimates from high-dimensional data with few samples.

arxiv:2605.12706 v1 · 2026-05-12 · cs.LG · q-bio.GN

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\pithnumber{HHEYAQE2W3MV5UW7UJGUJTG3QI}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

RSNet is the first R package to efficiently construct signed graphlet degree vector matrices (GDVMs) in near-constant time for sparse networks, providing scalable analysis of higher-order network structure.

C2weakest assumption

The resampling strategies (bootstrap, subsampling, cluster-based) sufficiently mitigate limited-sample-size issues and produce statistically reliable network estimates without introducing systematic bias or instability in high-dimensional regimes.

C3one line summary

RSNet is an R package that applies resampling strategies to robustly estimate Gaussian partial correlation networks and conditional Gaussian Bayesian networks from high-dimensional mixed data while adding efficient signed graphlet degree vector analysis for interpretability.

References

2 extracted · 2 resolved · 2 Pith anchors

[1] Honest confidence regions and optimality in high-dimensional precision matrix estimation 2001 · doi:10.48550/arxiv.1507.02061

[2] A Differential Degree Test for Comparing Brain Networks 2010 · doi:10.1145/3341161.3343692

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-18T03:09:49.612021Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

39c980409ab6d95ed2dfa24d44ccdb82212e1f47cd2d6f2eb2d78feb476f8f56

Aliases

arxiv: 2605.12706 · arxiv_version: 2605.12706v1 · doi: 10.48550/arxiv.2605.12706 · pith_short_12: HHEYAQE2W3MV · pith_short_16: HHEYAQE2W3MV5UW7 · pith_short_8: HHEYAQE2

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/HHEYAQE2W3MV5UW7UJGUJTG3QI \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 39c980409ab6d95ed2dfa24d44ccdb82212e1f47cd2d6f2eb2d78feb476f8f56

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "d0f15fa5fd049a09b54968e8837bdd36f890d6c88265593d068ca0f4fb57aae3",
    "cross_cats_sorted": [
      "q-bio.GN"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-12T20:08:46Z",
    "title_canon_sha256": "919d18b7094141a3b738c1cfa18044d482b05e0fce0c9743c47501fc742a1708"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12706",
    "kind": "arxiv",
    "version": 1
  }
}