Interesting. When I was in high school, I wrote some software to denoise datasets with a genetic algorithm (it's what we had before deep learning was a thing ;). I showed it to my math teachers and they were horrified; they told me that you cannot change data once it's been collected.

I realize now that their take is kind of wrong -- pretty much every instrument in the world performs filtering on what it samples before it presents you a number. Saying you can't filter data kind of misses the point, because almost every real-world system is bandwidth limited and acts as a low-pass filter. But sometimes there are different noise sources, and you can probably write an algorithm to attack them without being "inaccurate". (For example, ever measure very low voltages at relatively high frequency? You'll see a nice 60Hz component in there, because you are surrounded by a 60Hz electric field. That's noise, not data. Apparently averaging through multiple power line cycles is fine, but writing a program to do the same thing is wrong. Seems weird to me.)

Anyway, I'm still bitter about it. (That, and how in 4th grade I got a C in science because we had to make a flipbook about earthquakes that had to be titled "quakin' shakin' earth" and I spelled "quakin'" and "shakin'" wrong. Still don't know how to spell either of those contractions, or what flipbooks have to do with science. They don't come up in real life much. But I sure am bitter, 26 years later.)