@article {42438,
	title = {Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources},
	journal = {Sensors},
	volume = {22},
	year = {2022},
	month = {01-04-2022},
	pages = {2802},
	publisher = {MPDI},
	doi = {10.3390/s22072802},
	url = {https://www.mdpi.com/1424-8220/22/7/2802https://www.mdpi.com/1424-8220/22/7/2802/pdf},
	author = {Siri S. {Eide} and Riegler, Michael and Hugo Lewi {Hammer} and John Bj{\o}rnar {Bremnes}}
}
@inproceedings {28225,
	title = {Temperature Forecasting using Tower Networks},
	journal = {Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval},
	year = {2021},
	month = {08/2021},
	pages = {18-23},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	isbn = {9781450385299},
	doi = {10.1145/346394410.1145/3463944.3469099},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3463944https://dl.acm.org/doi/10.1145/3463944.3469099https://dl.acm.org/doi/pdf/10.1145/3463944.3469099},
	author = {Siri S. {Eide} and Riegler, Michael and Hugo Lewi {Hammer} and John Bj{\o}rnar {Bremnes}},
	editor = {Dao, Minh-Son and Dang-Nguyen, Duc-Tien and Riegler, Michael}
}
