Pith Number

pith:5Y7AWNYE

pith:2026:5Y7AWNYEPJHY5DNPC3CVU27ACF

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Neuro-Symbolic ODE Discovery with Latent Grammar Flow

Eleni Chatzi, Georgios Kissas, Karin Yu

Latent Grammar Flow discovers ODEs by placing grammar-based equation representations in a discrete latent space, using a behavioral loss to cluster similar equations, and sampling via a discrete flow model guided by data fit and constraints.

arxiv:2604.16232 v2 · 2026-04-17 · cs.LG · cs.AI · cs.CE · cs.SC

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\pithnumber{5Y7AWNYEPJHY5DNPC3CVU27ACF}

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Claims

C1strongest claim

We introduce Latent Grammar Flow (LGF), a neuro-symbolic generative framework for discovering ordinary differential equations from data. LGF embeds equations as grammar-based representations into a discrete latent space and forces semantically similar equations to be positioned closer together with a behavioural loss. Then, a discrete flow model guides the sampling process to recursively generate candidate equations that best fit the observed data.

C2weakest assumption

That a behavioral loss can reliably place semantically similar equations closer in the discrete latent space and that the discrete flow model can efficiently sample equations that both fit data and satisfy domain constraints without exhaustive search.

C3one line summary

Cited by

1 paper in Pith

Verifier-Guided Model Discovery for Physical Dynamical Systems with Pretrained Symbolic Transformers

Receipt and verification

First computed	2026-07-15T00:21:18.753364Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ee3e0b37047a4f8e8daf16c55a6be0114d0f963293c590b55b6dd352eaab8d17

Aliases

arxiv: 2604.16232 · arxiv_version: 2604.16232v2 · doi: 10.48550/arxiv.2604.16232 · pith_short_12: 5Y7AWNYEPJHY · pith_short_16: 5Y7AWNYEPJHY5DNP · pith_short_8: 5Y7AWNYE

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/5Y7AWNYEPJHY5DNPC3CVU27ACF \
  | 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: ee3e0b37047a4f8e8daf16c55a6be0114d0f963293c590b55b6dd352eaab8d17

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "0ab817126848b42d342b627b52fbed4443f45ddac0c5181d0c0580ecaeb05daf",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CE",
      "cs.SC"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-17T16:46:23Z",
    "title_canon_sha256": "e72b2d2f58748267d1db2aeaf078b0d5fc9003e2115268fc6678a8bc58e08f8b"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.16232",
    "kind": "arxiv",
    "version": 2
  }
}