Pith Number

pith:PTTWZOCR

pith:2026:PTTWZOCR6CTX5PHWKPCLSN5MZE

not attested not anchored not stored refs resolved

KAP-CPD: Kernel Aggregation for Change-Point Detection in Dynamic Networks

Hao Chen, Mingxuan Sun

Aggregating multiple kernels allows change-point detection in dynamic networks to work across unknown change patterns without distributional assumptions.

arxiv:2605.14463 v1 · 2026-05-14 · stat.ME

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{PTTWZOCR6CTX5PHWKPCLSN5MZE}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

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

KAP-CPD aggregates information from multiple kernels, allowing it to adapt to diverse change patterns. The proposed method does not assume specific underlying network distribution, and achieves strong empirical power across a wide range of network change scenarios.

C2weakest assumption

That the chosen set of kernels will collectively cover the unknown change patterns sufficiently well for the aggregation to retain high power without prior knowledge of the distribution.

C3one line summary

KAP-CPD aggregates multiple kernels into a distribution-free change-point test for dynamic networks and supplies a fast analytic implementation.

References

42 extracted · 42 resolved · 1 Pith anchors

[1] A survey of change point detection in dynamic graphs.IEEE Transactions on Knowledge and Data Engineering, 37(3):1030–1048, 2025 2025 · doi:10.1109/tkde.2024.3523857

[2] Bernhardt, Sara Larivière, Ezequiel Gleichgerrcht, Bernd J 2022 · doi:10.1111/epi.17171

[3] The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspec- tives.Frontiers in Network Physiology, V olume 3 - 2023, 2024 2023 · doi:10.3389/fnetp.2023.1338864

[4] Estimating whole-brain dynamics by using spectral clustering.Journal of the Royal Statistical Society Series C: Applied Statistics, 66(3):607–627, 09 2016 2016 · doi:10.1111/rssc.12169

[5] Predicting viral exposure response from modeling the changes of co-expression networks using time series gene expression data.BMC Bioinformatics, 21(1):370, August 2020 2020 · doi:10.1186/s12859-020-03705-0

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:06.755778Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

7ce76cb851f0a77ebcf653c4b937acc93d424f2be030de11dd1c9db2cdd3b15e

Aliases

arxiv: 2605.14463 · arxiv_version: 2605.14463v1 · doi: 10.48550/arxiv.2605.14463 · pith_short_12: PTTWZOCR6CTX · pith_short_16: PTTWZOCR6CTX5PHW · pith_short_8: PTTWZOCR

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/PTTWZOCR6CTX5PHWKPCLSN5MZE \
  | 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: 7ce76cb851f0a77ebcf653c4b937acc93d424f2be030de11dd1c9db2cdd3b15e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "b837643433c7f2a674514a8ec4ac9bd6789bee9fc228586b2b99a493cdc8bac7",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "stat.ME",
    "submitted_at": "2026-05-14T06:59:29Z",
    "title_canon_sha256": "15e559d18f124c9eb7e0dbd7d6e00ed9b0221330c415f916505222473416bb50"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14463",
    "kind": "arxiv",
    "version": 1
  }
}