Pith Number

pith:FDN7OREZ

pith:2026:FDN7OREZGSPZX745OKHNRNSVEL

not attested not anchored not stored refs resolved

Min Generalized Sliced Gromov Wasserstein: A Scalable Path to Gromov Wasserstein

Ashkan Shahbazi, Ping He, Soheil Kolouri, Xinran Liu

Min-GSGW learns coupled nonlinear slicers so that monotone 1D matching induces low-cost Gromov-Wasserstein transport plans in the original spaces.

arxiv:2605.13753 v1 · 2026-05-13 · cs.LG · cs.CV

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\pithnumber{FDN7OREZGSPZX745OKHNRNSVEL}

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Record completeness

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3 Author claim open · sign in to claim

4 Citations 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

min-GSGW produces meaningful geometric correspondences and GW objective values at substantially lower computational cost than existing GW solvers while remaining rigid-motion invariant.

C2weakest assumption

That the learned coupled nonlinear slicers produce push-forward values whose monotone coupling in the projected domain lifts to a transport plan whose GW cost in the original spaces is close to the true optimum.

C3one line summary

min-GSGW learns coupled nonlinear slicers to produce a rigid-motion-invariant, scalable approximation to the Gromov-Wasserstein distance and its transport plans.

References

26 extracted · 26 resolved · 1 Pith anchors

[1] On assignment problems related to gromov–wasserstein distances on the real line.SIAM Journal on Imaging Sciences, 16(2):1028–1032, 2023 2023

[2] ShapeNet: An Information-Rich 3D Model Repository 2015 · arXiv:1512.03012

[3] Differentiable generalized sliced wasserstein plans 2026

[4] Semidefinite relaxations of the gromov- wasserstein distance 2024

[5] Samir Chowdhury, David Miller, and Tom Needham. Quantized gromov-wasserstein, 2021 2021

Receipt and verification

First computed	2026-05-18T02:44:16.360799Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

28dbf74499349f9bff9d728ed8b65522d8174383a83ebc9cddddf8ef5850ff33

Aliases

arxiv: 2605.13753 · arxiv_version: 2605.13753v1 · doi: 10.48550/arxiv.2605.13753 · pith_short_12: FDN7OREZGSPZ · pith_short_16: FDN7OREZGSPZX745 · pith_short_8: FDN7OREZ

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/FDN7OREZGSPZX745OKHNRNSVEL \
  | 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: 28dbf74499349f9bff9d728ed8b65522d8174383a83ebc9cddddf8ef5850ff33

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "11e6114eaf33b48100f1bef876dcedbfd253623d73af4a3e1b16d84c317cced5",
    "cross_cats_sorted": [
      "cs.CV"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-13T16:33:10Z",
    "title_canon_sha256": "6cff6035d274f7a6362d72aafa62934a8a650a42aebc420d224e3b5bc122047f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13753",
    "kind": "arxiv",
    "version": 1
  }
}