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Ivan presents NN repair with preservation at ICCPS 2024
In the first presentation of ICCPS 2024, Ivan showcased a method to repair a neural network controller while preserving its verification results. Citation: Pengyuan Lu, Matthew Cleaveland, Oleg Sokolsky, Insup Lee, Ivan Ruchkin. Repairing Learning-Enabled Controllers While Preserving What Works [Arxiv] [Github] [Slides]. In Proceedings of the International Conference on Cyber-Physical Systems (ICCPS), Hong Kong, China, 2024.
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Language-enhanced OOD detection: new preprint online
Our paper gives users of autonomous cars the ability to describe in natural language what conditions they consider nominal or anomalous. Citation:
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F1/10 racing demo for the ECE External Advisory Board
Industry leaders visited the ECE department to witness the variety of work happening here. Thanks to everyone who helped, especially Carson Sobolewski and Lorant Domokos who led the demonstration. Some videos and photos from the event:
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First batch of students finishes the CURE racing course
Congratulations to the nine freshmen participants: Ramsey Makan, Jonas Dickens, Tyler Ruble, Christopher Oeltjen, Carter Amaba, Aditya Gandhi, Emilia Delaune, Ethan Krol, and Giancarlo Vidal! And a big thank you to the mentors: Ao Wang, Sam Jhong, Lorant Domokos, and Carson Sobolewski. More information on this CURE course is here.
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Foundation world models: new preprint online
Our paper develops training-free world models based on foundation models with interpretable latent states. Citation:
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TEA Lab moves to Malachowsky Hall
Now found in Malachowsky 4100, with a brand new racing track coming soon!
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Verifying high-dimensional controllers: new preprint online
Our new draft verifies image-based controllers by approximating them with several low-dimensional ones. Citation: Yuang Geng, Souradeep Dutta, Ivan Ruchkin. Bridging Dimensions: Confident Reachability for High-Dimensional Controllers [arxiv]. Preprint, in submission.
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Ivan participates in a panel on dependable space autonomy
Resolving Barriers to Infusion: Fielding Dependable Autonomous Space Systems at AIAA ASCEND 2023.
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Ivan serves on the PC of ICCPS’24 and AAAI’24
Consider submitting your papers there.
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How safe am I given what I see? New preprint online
Update: a poster was presented at UF AI Days 2023. This paper develops safety chance prediction for image-controlled autonomous systems with calibration guarantees. Citation: Zhenjiang Mao, Carson Sobolewski, Ivan Ruchkin. How Safe Am I Given What I See? Calibrated Prediction of Safety Chances for Image-Controlled Autonomy [arxiv]. Preprint, in submission.