most citedDigital Twin Earth -- Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators

20 citations · 23 across the 2 of their papers we have counts for

collaborators

5 papers

physics.ao-ph202120 cited

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…

cs.CV20213 cited

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…

cs.LG2021

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…

cs.CV2020

Physics-informed GANs for Coastal Flood Visualization

Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa +8

As climate change increases the intensity of natural disasters, society needs better tools for adaptation. Floods, for example, are the most frequent natural disaster, but during h…

cs.SE2020

Technology Readiness Levels for AI & ML

Alexander Lavin, Gregory Renard

The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence…