{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:18:50Z","timestamp":1750220330754,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T00:00:00Z","timestamp":1629504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,21]]},"DOI":"10.1145\/3463944.3469099","type":"proceedings-article","created":{"date-parts":[[2021,8,20]],"date-time":"2021-08-20T01:59:32Z","timestamp":1629424772000},"page":"18-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Temperature Forecasting using Tower Networks"],"prefix":"10.1145","author":[{"given":"Siri S.","family":"Eide","sequence":"first","affiliation":[{"name":"Norwegian Meteorological Institute, Oslo, Norway"}]},{"given":"Michael A.","family":"Riegler","sequence":"additional","affiliation":[{"name":"SimulaMet, Oslo, Norway"}]},{"given":"Hugo L.","family":"Hammer","sequence":"additional","affiliation":[{"name":"Oslo Metropolitan University, Oslo, Norway"}]},{"given":"John Bj\u00f8rnar","family":"Bremnes","sequence":"additional","affiliation":[{"name":"Norwegian Meteorological Institute, Oslo, Norway"}]}],"member":"320","published-online":{"date-parts":[[2021,8,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall. arxiv","author":"Adewoyin Rilwan","year":"2008","unstructured":"Rilwan Adewoyin , Peter Dueben , Peter Watson , Yulan He , and Ritabrata Dutta . 2021. TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall. arxiv : 2008 .09090 [cs.CE] Rilwan Adewoyin, Peter Dueben, Peter Watson, Yulan He, and Ritabrata Dutta. 2021. TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall. arxiv: 2008.09090 [cs.CE]"},{"key":"e_1_3_2_1_2_1","volume-title":"Machine Learning for Precipitation Nowcasting from Radar Images. arxiv","author":"Agrawal Shreya","year":"1912","unstructured":"Shreya Agrawal , Luke Barrington , Carla Bromberg , John Burge , Cenk Gazen , and Jason Hickey . 2019. Machine Learning for Precipitation Nowcasting from Radar Images. arxiv : 1912 .12132 [cs.CV] Shreya Agrawal, Luke Barrington, Carla Bromberg, John Burge, Cenk Gazen, and Jason Hickey. 2019. Machine Learning for Precipitation Nowcasting from Radar Images. arxiv: 1912.12132 [cs.CV]"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5194\/gmd-11-3999-2018"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1175\/WAF-D-19-0030.1"},{"key":"e_1_3_2_1_5_1","volume-title":"Deep learning for short-term temperature forecasts with video prediction methods. (March","author":"Gong Bing","year":"2020","unstructured":"Bing Gong , Severin Hu\u00dfmann , Amirpasha Mozaffari , Jan Vogelsang , and Martin Schultz . 2020. Deep learning for short-term temperature forecasts with video prediction methods. (March 2020 ). https:\/\/doi.org\/10.5194\/egusphere-egu2020--17748 10.5194\/egusphere-egu2020--17748 Bing Gong, Severin Hu\u00dfmann, Amirpasha Mozaffari, Jan Vogelsang, and Martin Schultz. 2020. Deep learning for short-term temperature forecasts with video prediction methods. (March 2020). https:\/\/doi.org\/10.5194\/egusphere-egu2020--17748"},{"key":"e_1_3_2_1_6_1","unstructured":"Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative Adversarial Networks. arxiv: 1406.2661 [stat.ML]  Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative Adversarial Networks. arxiv: 1406.2661 [stat.ML]"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2015.7280812"},{"key":"e_1_3_2_1_8_1","volume-title":"Suykens","author":"Karevan Zahra","year":"2018","unstructured":"Zahra Karevan and Johan A. K . Suykens . 2018 . Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting . arxiv: 1811.06341 [cs.LG] Zahra Karevan and Johan A. K. Suykens. 2018. Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting. arxiv: 1811.06341 [cs.LG]"},{"key":"e_1_3_2_1_9_1","unstructured":"Diederik P Kingma and Max Welling. 2014. Auto-Encoding Variational Bayes. arxiv: 1312.6114 [stat.ML]  Diederik P Kingma and Max Welling. 2014. Auto-Encoding Variational Bayes. arxiv: 1312.6114 [stat.ML]"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2020.100007"},{"key":"e_1_3_2_1_11_1","volume-title":"Stochastic Adversarial Video Prediction. arxiv","author":"Lee Alex X.","year":"1804","unstructured":"Alex X. Lee , Richard Zhang , Frederik Ebert , Pieter Abbeel , Chelsea Finn , and Sergey Levine . 2018. Stochastic Adversarial Video Prediction. arxiv : 1804 .01523 [cs.CV] Alex X. Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine. 2018. Stochastic Adversarial Video Prediction. arxiv: 1804.01523 [cs.CV]"},{"key":"e_1_3_2_1_12_1","first-page":"3","article-title":"The predictability of a flow which possesses many scales of motion","volume":"21","author":"EDWARD N.","year":"1969","unstructured":"EDWARD N. LORENZ. 1969 . The predictability of a flow which possesses many scales of motion . Tellus , Vol. 21 , 3 (June 1969), 289--307. https:\/\/doi.org\/10.1111\/j.2153--3490.1969.tb00444.x 10.1111\/j.2153--3490.1969.tb00444.x EDWARD N. LORENZ. 1969. The predictability of a flow which possesses many scales of motion. Tellus, Vol. 21, 3 (June 1969), 289--307. https:\/\/doi.org\/10.1111\/j.2153--3490.1969.tb00444.x","journal-title":"Tellus"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1175\/BAMS-D-18-0237.A"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.49"},{"key":"e_1_3_2_1_15_1","volume-title":"Wai kin Wong, and Wang chun Woo","author":"Shi Xingjian","year":"2015","unstructured":"Xingjian Shi , Zhourong Chen , Hao Wang , Dit-Yan Yeung , Wai kin Wong, and Wang chun Woo . 2015 . Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting . arxiv: 1506.04214 [cs.CV] Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai kin Wong, and Wang chun Woo. 2015. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. arxiv: 1506.04214 [cs.CV]"},{"key":"e_1_3_2_1_16_1","volume-title":"MetNet: A Neural Weather Model for Precipitation Forecasting. arxiv","author":"S\u00f8nderby Casper Kaae","year":"2003","unstructured":"Casper Kaae S\u00f8nderby , Lasse Espeholt , Jonathan Heek , Mostafa Dehghani , Avital Oliver , Tim Salimans , Shreya Agrawal , Jason Hickey , and Nal Kalchbrenner . 2020. MetNet: A Neural Weather Model for Precipitation Forecasting. arxiv : 2003 .12140 [cs.LG] Casper Kaae S\u00f8nderby, Lasse Espeholt, Jonathan Heek, Mostafa Dehghani, Avital Oliver, Tim Salimans, Shreya Agrawal, Jason Hickey, and Nal Kalchbrenner. 2020. MetNet: A Neural Weather Model for Precipitation Forecasting. arxiv: 2003.12140 [cs.LG]"}],"event":{"name":"ICMR '21: International Conference on Multimedia Retrieval","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Taipei Taiwan","acronym":"ICMR '21"},"container-title":["Proceedings of the 2021 ACM Workshop on Intelligent Cross-Data Analysis and Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3463944.3469099","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3463944.3469099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:15Z","timestamp":1750191135000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3463944.3469099"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,21]]},"references-count":16,"alternative-id":["10.1145\/3463944.3469099","10.1145\/3463944"],"URL":"https:\/\/doi.org\/10.1145\/3463944.3469099","relation":{},"subject":[],"published":{"date-parts":[[2021,8,21]]},"assertion":[{"value":"2021-08-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}