pith:PLY6JTRC
Exact Fixed-Point Constraints in Neural-ODEs with Provable Universality
Neural-ODEs can approximate arbitrary velocity fields while exactly forcing velocity to zero at any finite set of prescribed points.
arxiv:2605.10613 v1 · 2026-05-11 · cond-mat.dis-nn · cs.LG · physics.bio-ph
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Record completeness
Claims
We rigorously prove the universality of the Neural-ODE under any local constraints in the velocity field and give a computationally convenient way of imposing the fixed points.
That the explicit accommodation for fixed points can be introduced without reducing the expressive power of the underlying Neural-ODE architecture.
A technique plants exact fixed points in Neural-ODE velocity fields with a rigorous proof that universality is preserved under local constraints.
References
Formal links
Receipt and verification
| First computed | 2026-06-23T03:14:29.043179Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
7af1e4ce22ee6710d5407320c8463116b770d4f1cfdfe517b3b2fee3cd883a07
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/PLY6JTRC5ZTRBVKAOMQMQRRRC2 \
| 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: 7af1e4ce22ee6710d5407320c8463116b770d4f1cfdfe517b3b2fee3cd883a07
Canonical record JSON
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