3 papers
cs.LG2026
Towards a Foundation-Model Paradigm for Aerodynamic Prediction in Three-dimensional Design
Yunjia Yang, Babak Gholami, Caglar Gurbuz +2
Accurate machine-learning models for aerodynamic prediction are essential for accelerating shape optimization, yet remain challenging to develop for complex three-dimensional confi…
cs.CV2025
Forecasting Continuous Non-Conservative Dynamical Systems in SO(3)
Lennart Bastian, Mohammad Rashed, Nassir Navab +1
Modeling the rotation of moving objects is a fundamental task in computer vision, yet extrapolation still presents numerous challenges: (1) unknown quantities such as the m…
cs.CV2025
Continuous-Time SO(3) Forecasting with Savitzky--Golay Neural Controlled Differential Equations
Lennart Bastian, Mohammad Rashed, Nassir Navab +1
Tracking and forecasting the rotation of objects is fundamental in computer vision and robotics, yet SO(3) extrapolation remains challenging as (1) sensor observations can be noisy…