Connecting numerical simulation and machine learning: How to bridge the gap between theory and reality?

被引：0
|
作者：
Piprek, Joachim [1 ]
机构：
[1] NUSOD Inst LLC, Newark, DE 19714 USA
来源：
2020 INTERNATIONAL CONFERENCE ON NUMERICAL SIMULATION OF OPTOELECTRONIC DEVICES (NUSOD) | 2020年
关键词：
machine learning; deep learning; neural networks; artificial intelligence; numerical simulation; semiconductor; optoelectronic devices; photonics; INVERSE DESIGN;
D O I：
10.1109/nusod49422.2020.9217746
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Machine learning and numerical simulation represent opposite approaches to computational analysis of the real world, inductive vs. deductive. However, both methods suffer from various uncertainties and even their combination often fails to link theory and reality. This paper presents a critical review of such connections and proposes improvement options for optoelectronic devices.
引用
收藏
页码：105 / 106
页数：2
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