2021
Adjusting for Autocorrelated Errors in Neural Networks for Time Series
NeurIPS 2021poster
An increasing body of research focuses on using neural networks to model time series. A common assumption in training neural networks via maximum likelihood estimation on time series is that the errors across time steps are uncorrelated. However, errors are actually autocorrelated in many cases due…