5 papers
PINN-Cast: Exploring the Role of Continuous-Depth NODE in Transformers and Physics Informed Loss as Soft Physical Constraints in Short-term Weather Forecasting
Hira Saleem, Flora Salim, Cormac Purcell
Operational weather prediction has long relied on physics-based numerical weather prediction (NWP), whose accuracy comes at the cost of substantial compute and complex simulation w…
Thermal Anomaly Detection using Physics Aware Neuromorphic Networks: Comparison between Raw and L1C Sentinel-2 Data
Stephen Smith, Cormac Purcell, Gabriele Meoni +2
Damage caused by bushfires and volcanic eruptions escalates rapidly when detection is delayed, making fast and reliable early warning capabilities essential. Recent Earth Observati…
A-UTE: Advection Informed, Uncertainty Aware Temperature Emulator
Hira Saleem, Flora Salim, Cormac Purcell
Physics-based Earth system models (ESMs) are essential for attributing climate change and generating scenario projections, yet their reliance on high-resolution numerical integrati…
STC-ViT: Spatio Temporal Continuous Vision Transformer for Medium-range Global Weather Forecasting
Hira Saleem, Flora Salim, Cormac Purcell
Operational Numerical Weather Prediction (NWP) system relies on computationally expensive physics-based models. Recently, transformer models have shown remarkable potential in weat…
Training-free AI for Earth Observation Change Detection using Physics Aware Neuromorphic Networks
Stephen Smith, Cormac Purcell, Zdenka Kuncic
Earth observations from low Earth orbit satellites provide vital information for decision makers to better manage time-sensitive events such as natural disasters. For the data to b…