Little need to speculate in this case: they're trying to fit giant models on a dataset that's a fraction of a megabyte, without any targeted pretraining or prior. That's like trying to prove trains are slower than running humans by having the two compete in a 100m race from standstill. The biggest set (monthly observations) is around 105kB of data. If anyone is surprised your average 10GB+ network doesn't perform very well there, well... I suppose now you know.
TropicalAudio t1_iylsprn wrote
Reply to comment by marr75 in [R] Statistical vs Deep Learning forecasting methods by fedegarzar
Little need to speculate in this case: they're trying to fit giant models on a dataset that's a fraction of a megabyte, without any targeted pretraining or prior. That's like trying to prove trains are slower than running humans by having the two compete in a 100m race from standstill. The biggest set (monthly observations) is around 105kB of data. If anyone is surprised your average 10GB+ network doesn't perform very well there, well... I suppose now you know.