Our datasets and code are available via the following links: Github: https://github.com/NREL/BuildingsBench As described in Sec. 3 and Sec. 4, Buildings-900K and the BuildingsBench benchmark datasets are B.1 Motivation Q: For what purpose was the dataset created? It specifically addresses a lack of appropriately sized and diverse datasets for pretraining STLF models. We emphasize that the EULP was not originally developed for studying STLF. Rather, it was developed as a general resource to "...help electric utilities, grid operators, manufacturers, Q: Who created the dataset (e.g., which team, research group) and on behalf of which entity Q: Who funded the creation of the dataset?

Short-term load forecasting (STLF), which typically ranges from hour-ahead to a few days ahead, plays a multitude of critical roles.

But not in the way Fukushima's geneticists thought. Breakthroughs, discoveries, and DIY tips sent six days a week. In the regions surrounding the Fukushima nuclear plant disaster in northeast Japan, radioactive domestic pigs and wild boar are rapidly interbreeding. While far from the only recent incident of animal hybridization, the situation is presenting wildlife biologists with an unprecedented opportunity to examine the issue in real-time, as well as provide a template for studying the growing problem worldwide. In 2011, a 9.0 magnitude undersea earthquake in the Pacific Ocean rocked Japan.

Spiking neural networks (SNNs) represent a promising approach to developing artificial neural networks that are both energy-efficient and biologically plausible.