A history-conditioned physics-informed flow-matching framework for probabilistic dynamics prediction of tendon-driven continuum robots, addressing uncertainties from material behavior, tendon transmission, friction, and contact.
See LICENSE fileContinuum RobotFlow MatchingProbabilistic Dynamics
A comprehensive benchmark dataset for training and evaluating neural PDE solvers, containing six standard tasks on regular grids, structured grids, and irregular geometries, used for unified evaluation in the ICML 2024 paper Transolver.
Gnomon introduces a physics-informed system that reconstructs LEO satellite serving geometry and signal attenuation to forecast user-perceived downlink/uplink throughput and RTT under varying trace availability.
See LICENSE fileLEO satellitePhysics-Informed Neural Networklink prediction
