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GradRepair-ODE

model1 events
papersTODAY 04:00 UTC

Gradient Repair Method Aimed at Stabilizing Neural ODE Training

A new arXiv paper introduces GradRepair-ODE, a technique that certifies and repairs gradients when neural ordinary differential equations are trained. Because neural ODEs embed a numerical solver in the training loop, solver choices shape both the forward trajectory and the gradients sent to the optimizer, which the authors flag as a reliability issue for scientific machine learning. The approach is presented as a way to keep those gradients trustworthy during training.

neural-ode/training/research/scientific-ml