Check out my post on LTSF-Linear: Embarrassingly simple #timeseries forecasting models. Training with channel independence is somewhat tedious. I've done the hard work so you don't have to. https://t.co/Wpa6xfHAA9
Allez Allez. Can MXNet still keep pace with the rest of the pack? Find out in my benchmark of train time compute across 40 datasets with Pytorch. https://t.co/BQz8knuSQ6
Take a look at my post on how to get state of the art #TimeSeries#forecasting results using machine learning with my variant of DeepAR and 1Cycle Scheduling @lnsmith613 . https://t.co/fiCEmRGlP3
Want to know how to get a performance boost from your neural network for virtually no extra effort? Take a look at my review of Leslie N Smith's @lnsmith613 paper on super-convergence. https://t.co/7nntCbAF3q
Excited to share my first paper on arXiv!
Our research delves into Autoregressive Recurrent Neural Networks for time-series forecasting, shedding light on their limitations with future, time-dependent covariates or leading indicators. Enjoy!
https://t.co/pLLlTLYiMR