Low-Dimensional Graph Embeddings for Representing Semiconductor Manufacturing States

Reinforcement learning in manufacturing requires state representations that capture complex, dynamic interdependencies while remaining computationally efficient. Traditional feature selection often loses critical information, and existing graph-based

Publication Details

Published
2025-10-14
DOI
https://doi.org/10.36227/techrxiv.176046343.38977267/v1
Primary Topic
Archaeology and Historical Studies
Type
article
Field-Weighted Citation Impact
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article

Low-Dimensional Graph Embeddings for Representing Semiconductor Manufacturing States

Archaeology and Historical Studies
article

Low-Dimensional Graph Embeddings for Representing Semiconductor Manufacturing States

article en

Abstract

Reinforcement learning in manufacturing requires state representations that capture complex, dynamic interdependencies while remaining computationally efficient. Traditional feature selection often loses critical information, and existing graph-based

Openalex Percentile: Top 39%
Archaeology and Historical Studies
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Low-Dimensional Graph Embeddings for Representing Semiconductor Manufacturing States · (2025) | TGRS Research Map | TGRS