pith:HI5THGUT
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
Decision trees correspond to diffusion processes in limiting regimes and share the Global Trajectory Score Matching optimization principle.
arxiv:2605.00414 v2 · 2026-05-01 · cs.LG · cond-mat.stat-mech · cs.AI
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Claims
establishing a crisp mathematical correspondence between hierarchical decision trees and diffusion processes in appropriate limiting regimes. Our unification reveals a shared optimization principle: Global Trajectory Score Matching (GTSM), for which gradient boosting (in an idealized version) is asymptotically optimal.
The limiting regimes invoked for the correspondence are appropriate and yield a meaningful practical unification without additional unstated assumptions that would break the link between trees and diffusion processes.
Decision trees and diffusion models are unified through limiting-regime correspondence under Global Trajectory Score Matching, yielding TreeFlow for competitive tabular generation with 2x speedup and DSMTREE for distilling tree logic into neural nets with near-teacher performance.
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| First computed | 2026-05-22T01:04:03.843430Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/HI5THGUT2R3FD4HIZHOQGOZUNT \
| 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())"
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Canonical record JSON
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