Per this deep learning book I am reading:
In general, with neural networks, it’s safe to input missing values as 0, with the condition that 0 isn’t already a meaningful value. The network will learn from exposure to the data that the value 0 means missing data and will start ignoring the value.
However, let's say 0 is meaningful. What should I do instead? What if I give it like a large value like 10000?