We are back from the summer break. In this episode, Peter Seeberg talks to Prof. Dr. Oliver Niggemann about his study Robustness and Generalization Performance of Deep Learning Models on Cyber-Physical Systems.
Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.
We thank our partner <a href="https://new.siemens.com/global/en/products/automation/topic-areas/artificial-intelligence-in-industry.html">Siemens </a>
Olivers Paper: <a href="https://arxiv.org/abs/2306.07737">https://arxiv.org/abs/2306.07737</a>
Thanks to Women in AI and Robotics (<a href="https://www.womeninairobotics.de/">more</a>)
PLEASE fill out the survey from Gabriel Krummenacher and the ETH Zurich
<a href="https://www.zuehlke.com/en/machine-learning">https://www.zuehlke.com/en/machine-learning</a>
We thank our team:
Barbara, Anne and Simon!

We are back from the summer break. In this episode, Peter Seeberg talks to Prof. Dr. Oliver Niggemann about his study Robustness and Generalization Performance of Deep Learning Models on Cyber-Physical Systems. Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co. We thank our partner Siemens Olivers Paper: https://arxiv.org/abs/2306.07737 Thanks to Women in AI and Robotics (more) PLEASE fill out the survey from Gabriel Krummenacher and the ETH Zurich https://www.zuehlke.com/en/machine-learning We thank our team: Barbara, Anne and Simon!

We are back from the summer break. In this episode, Peter Seeberg talks to Prof. Dr. Oliver Niggemann about his study Robustness and Generalization Performance of Deep Learning Models on Cyber-Physical Systems.
Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.
We thank our partner <a href="https://new.siemens.com/global/en/products/automation/topic-areas/artificial-intelligence-in-industry.html" rel="noopener noreferrer">Siemens </a>
Olivers Paper: <a href="https://arxiv.org/abs/2306.07737" rel="noopener noreferrer">https://arxiv.org/abs/2306.07737</a>
Thanks to Women in AI and Robotics (<a href="https://www.womeninairobotics.de/" rel="noopener noreferrer">more</a>)
PLEASE fill out the survey from Gabriel Krummenacher and the ETH Zurich
<a href="https://www.zuehlke.com/en/machine-learning" rel="noopener noreferrer">https://www.zuehlke.com/en/machine-learning</a>
We thank our team:
Barbara, Anne and Simon!

Robustness and generalization performance of Deep Learning Models on Cyber-Physical Systems

The Industrial AI Podcast reports weekly on the latest developments in AI and machine learning for the engineering, robotics, automotive, process and automation industries. The podcast features industrial users, scientists, vendors and startups in the field of Industrial AI and machine learning. The podcast is hosted by Peter Seeberg, Industrial AI consultant and Robert Weber, tech journalist.Their mission: Demystify Industrial AI and machine learning, inspire industrial users.

The hosts: 

Peter Seeberg is an Industrial AI and machine learning expert for the manufacturing industry. He worked over 25 years in IT (Intel) and 10 years in Automation. He co-initiated the Industrial Data Intelligence Startup (Softing) where he was responsible for managing machine learning projects in industrial environments. Today he advises companies when it comes to Industrial AI and machine learning. Together with Robert Weber, journalist for industrial topics, he discusses AI and ML applications, standards, and education topics, make or buy decisions as well as regulation for AI in manufacturing.

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The Industrial AI Podcast reports weekly on the latest developments in AI and machine learning for the engineering, robotics, automotive, process and automation industries. The podcast features industrial users, scientists, vendors and startups in the field of Industrial AI and machine learning. The podcast is hosted by Peter Seeberg, Industrial AI consultant and Robert Weber, tech journalist.Their mission: Demystify Industrial AI and machine learning, inspire industrial users. The hosts: Peter Seeberg is an Industrial AI and machine learning expert for the manufacturing industry. He worked over 25 years in IT (Intel) and 10 years in Automation. He co-initiated the Industrial Data Intelligence Startup (Softing) where he was responsible for managing machine learning projects in industrial environments. Today he advises companies when it comes to Industrial AI and machine learning. Together with Robert Weber, journalist for industrial topics, he discusses AI and ML applications, standards, and education topics, make or buy decisions as well as regulation for AI in manufacturing.

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Robustness and generalization performance of Deep Learning Models on Cyber-Physical Systems

Robustness and generalization performance of Deep Learning Models on Cyber-Physical Systems

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