Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport

Researchers introduce Hyperparameter Trajectory Inference (HTI), a method to predict how neural networks behave with different hyperparameter settings without expensive retraining. The approach uses conditional Lagrangian optimal transport to create surrogate models that approximate neural network outputs across various hyperparameter configurations.