Pith Number

pith:PCTROGYU

pith:2026:PCTROGYUD4JEZPARU4NYP4OBUG

not attested not anchored not stored refs resolved

Diversified Residual Symbolic Regression

Koki Ikeda, Masahiro Nomura, Ryoki Hamano

Symbolic regression now collects multiple expressions that differ in which observations they treat as outliers.

arxiv:2605.15809 v1 · 2026-05-15 · cs.NE

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\usepackage{pith}
\pithnumber{PCTROGYUD4JEZPARU4NYP4OBUG}

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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

On a synthetic mixture dataset, DRSR produces more diverse expressions than conventional SR while capturing multiple underlying relationships. On a real-world astronomical dataset, DRSR discovers multiple expressions consistent with known physical relationships.

C2weakest assumption

That diversity in residual patterns produced by the Quality-Diversity archive corresponds to distinct, meaningful underlying relationships that domain experts can reliably distinguish and select among, rather than superficial variations.

C3one line summary

DRSR uses Quality-Diversity to produce diverse symbolic regression expressions differing in residual distributions, enabling post-search selection on synthetic and astronomical data.

References

37 extracted · 37 resolved · 4 Pith anchors

[1] 2014.Segmentation, Revenue Management, and Pricing Analytics 2014

[2] Jean-Philippe Bruneton. 2025. Enhancing Symbolic Regression with Quality- Diversity and Physics-Inspired Constraints. doi:10.48550/arXiv.2503.19043 2025 · doi:10.48550/arxiv.2503.19043

[3] Exploration and Exploitation in Symbolic Regression using Quality-Diversity and Evolutionary Strategies Algorithms 2019 · doi:10.48550/arxiv.1906.03959

[4] Pedro Cardoso, Vasco V. Branco, Paulo A.V. Borges, José C. Carvalho, François Rigal, Rosalina Gabriel, Stefano Mammola, José Cascalho, and Luís Correia. 2020. Automated Discovery of Relationships, Mod 2020 · doi:10.3389/fevo.2020.530135

[5] Niels Johan Christensen, Samuel Demharter, Meera Machado, Lykke Pedersen, Marco Salvatore, Valdemar Stentoft-Hansen, and Miquel Tri- ana Iglesias. 2022. Identifying interactions in omics data for clin 2022 · doi:10.1093/bioinformatics/btac405

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:01:19.672265Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

78a7171b141f124cbc11a71b87f1c1a1985ae71b5d1b58a0f0e79bf1d016286d

Aliases

arxiv: 2605.15809 · arxiv_version: 2605.15809v1 · doi: 10.48550/arxiv.2605.15809 · pith_short_12: PCTROGYUD4JE · pith_short_16: PCTROGYUD4JEZPAR · pith_short_8: PCTROGYU

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/PCTROGYUD4JEZPARU4NYP4OBUG \
  | 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: 78a7171b141f124cbc11a71b87f1c1a1985ae71b5d1b58a0f0e79bf1d016286d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e69a208e11fbcd24185a19d1f5bf769754d6d649a04d9f1b8aa53ccbc9cf20b5",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.NE",
    "submitted_at": "2026-05-15T10:04:03Z",
    "title_canon_sha256": "25ceed6329a7c42b748294a92716ef7bb681f23daa953a296d6192c2dbcc355d"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.15809",
    "kind": "arxiv",
    "version": 1
  }
}