The decode() function, in the highwayNet class, is the one returning the future trajectory predicted. Before returning the trajectory, fut_pred is modified by outputActivation() in utils.py.
The return value of outputActivation() is a concatenation of muX, muY, sigX, sigY and rho. The comment above tells us this output layer comes from Graves, 2015 but I don't understand the meaning of these 5 variables.
Can you explain to me the meaning of these variables?
I think it's mu for mean, sig for standard deviation, and rho for the correlation. sig is actually the reciprocal of the real sig though, according to #23.
The
decode()
function, in the highwayNet class, is the one returning the future trajectory predicted. Before returning the trajectory,fut_pred
is modified byoutputActivation()
in utils.py. The return value ofoutputActivation()
is a concatenation ofmuX
,muY
,sigX
,sigY
andrho
. The comment above tells us this output layer comes from Graves, 2015 but I don't understand the meaning of these 5 variables.Can you explain to me the meaning of these variables?