2 papers
physics.comp-ph2020
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics
Li Li, Stephan Hoyer, Ryan Pederson +4
Including prior knowledge is important for effective machine learning models in physics, and is usually achieved by explicitly adding loss terms or constraints on model architectur…
cs.LG2020
Using a thousand optimization tasks to learn hyperparameter search strategies
Luke Metz, Niru Maheswaranathan, Ruoxi Sun +3
We present TaskSet, a dataset of tasks for use in training and evaluating optimizers. TaskSet is unique in its size and diversity, containing over a thousand tasks ranging from ima…