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JAREX: An Acquisition Function for Multi-Objective Algorithmic Process Characterization

Paper recorded by Signals 4 on 2026-09-21 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.LG · 机器学习 · first seen 2026-09-22

Abstract

Pharmaceutical process characterization is central to Quality by Design because it defines how variations in process parameters affect the ability to meet product quality specifications, thereby supporting proven acceptable ranges and robust manufacturing. In practice, however, characterization still relies largely on factorial design of experiments (DOE) approaches, which are inefficient for reso

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#4 most recent of 250 cs.LG papers we have recorded · ↑ newer: LoRA-generating hypernetworks for efficient on-device LLM generative p · ↓ older: Learning Physics from an Imperfect Ancestor
Cite this page: JAREX: An Acquisition Function for Multi-Objective Algorithmic Process Characterization: the #4 most recent of 250 cs.LG papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/jarex-an-acquisition-function-for-multi-objective-algorithmic-process-characteri.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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