189 citations · 328 across the 10 of their papers we have counts for
5 papers · 1 filter
Digital Twin Earth -- Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators
Peishi Jiang, Nis Meinert, Helga Jordão +8
Developing fast and accurate surrogates for physics-based coastal and ocean models is an urgent need due to the coastal flood risk under accelerating sea level rise, and the comput…
WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data
Rupa Kurinchi-Vendhan, Björn Lütjens, Ritwik Gupta +2
The transition to green energy grids depends on detailed wind and solar forecasts to optimize the siting and scheduling of renewable energy generation. Operational forecasts from n…
PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation in Ocean Modeling
Björn Lütjens, Catherine H. Crawford, Mark Veillette +1
Climate models project an uncertainty range of possible warming scenarios from 1.5 to 5 degree Celsius global temperature increase until 2100, according to the CMIP6 model ensemble…
Generating Physically-Consistent Satellite Imagery for Climate Visualizations
Björn Lütjens, Brandon Leshchinskiy, Océane Boulais +11
Deep generative vision models are now able to synthesize realistic-looking satellite imagery. But, the possibility of hallucinations prevents their adoption for risk-sensitive appl…
Technology Readiness Levels for Machine Learning Systems
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic +12
The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of dilig…