Weather4cast - Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts

Aleksandra Gruca · Pedro Herruzo · Pilar Rípodas · Xavier Calbet · Llorenç Lliso Valverde · Federico Serva · Bertrand Le Saux · Michael Kopp · David Kreil · Sepp Hochreiter

[ Abstract ] [ Website ]
Thu 8 Dec 3 a.m. PST — 6:30 a.m. PST


The Weather4cast NeurIPS Competition has high practical impact for society: Unusual weather is increasing all over the world, reflecting ongoing climate change, and affecting communities in agriculture, transport, public health and safety, etc.Can you predict future rain patterns with modern machine learning algorithms? Apply spatio-temporal modelling to complex dynamic systems. Get access to unique large-scale data and demonstrate temporal and spatial transfer learning under strong distributional shifts.We provide a super-resolution challenge of high relevance to local events: Predict future weather as measured by ground-based hi-res rain radar weather stations.In addition to movies comprising rain radar maps you get large-scale multi-band satellite sensor images for exploiting data fusion.Winning models will advance key areas of methods research in machine learning, of relevance beyond the application domain.