Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
In many machine learning applications, labeled data is scarce and obtaining more labels is expensive. We introduce a new approach to supervising neural networks by specifying constraints that should hold over the output space, rather than direct examples of input-output pairs. These constraints are derived from prior domain knowledge, e.g., …