226 citations · 272 across the 15 of their papers we have counts for
4 papers · 1 filter
A Safe Preference Learning Approach for Personalization with Applications to Autonomous Vehicles
Ruya Karagulle, Nikos Arechiga, Andrew Best +2
This work introduces a preference learning method that ensures adherence to given specifications, with an application to autonomous vehicles. Our approach incorporates the priority…
Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge
Anna Kawakami, Luke Guerdan, Yanghuidi Cheng +6
A growing body of research has explored how to support humans in making better use of AI-based decision support, including via training and onboarding. Existing research has focuse…
Drag-guided diffusion models for vehicle image generation
Nikos Arechiga, Frank Permenter, Binyang Song +1
Denoising diffusion models trained at web-scale have revolutionized image generation. The application of these tools to engineering design is an intriguing possibility, but is curr…
Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings
Binyang Song, Chenyang Yuan, Frank Permenter +2
Generative AI models have made significant progress in automating the creation of 3D shapes, which has the potential to transform car design. In engineering design and optimization…