to be sparse through this RZ which could be another one norm and then you reconstruct the d adwords this is in the general form of regular risotto encoder in this particular form of an l1 regularizer that's called a sparse o2 encoder now these two forms of it a form where is just a neural net with an additional term in the in the objective function for training is another form where you still have Z as a written variable but now you have a third term in the energy that makes you pay for making z2 different from the output of