模型可解释性

Sep 16, 2022·
Shenghui (Samuel) Gu
Shenghui (Samuel) Gu
· 1 min read
Abstract
简单介绍模型的可解释性。
Date
Sep 16, 2022 4:00 PM — 5:00 PM
Event
Meituan internal sharing session
Location

Meituan

221 Huangxing Road, Yangpu District, Shanghai, Shanghai 200082

events

简单介绍模型的可解释性。

参考的这位 UP 主的视频【一起啃书】Interpretable Machine Learning，建议去看看。

Explainable AI
Shenghui (Samuel) Gu
Authors
Shenghui (Samuel) Gu (he/him)
Researcher in Trustworthy AI and Software Engineering
I build methods for testing, validating, and improving trustworthy AI-enabled software systems. My research lies at the intersection of Software Engineering, AI Safety, and System Reliability, spanning LLM-driven testing, search-based software engineering for autonomous systems, and AIOps for distributed architectures. A central theme of my work is to make generative AI useful, interpretable, and dependable for solving complex validation problems in safety-critical and large-scale industrial systems.