arXiv (All)
open access
Structure-Adaptive Tree Field Integrators
computer-vision-and-pattern-recognitiondata-structures-and-algorithmsnumerical-analysisoptimization-and-control
We present a new class of near-linear algorithms for efficiently integrating general tensor fields defined on trees with distance dependent kernels, the Structure-Adaptive Tree Field Integrators (STAD-TFIs). STAD-TFIs exploit the tree's underlying structure through decompositions built around path b
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Two-loop tensor integral reduction for automated tools#625303
- Two-loop tensor integral reduction for automated tools#623030
- Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction#973451
- Improved Gradient Descent Lower Bounds Beyond Nesterov#632824
- Rerootable Hypertree Decompositions#463301
Record · ID 1119098
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive