455 citations · 474 across the 6 of their papers we have counts for
12 papers
Generative Modeling of High-resolution Global Precipitation Forecasts
James Duncan, Shashank Subramanian, Peter Harrington
Forecasting global precipitation patterns and, in particular, extreme precipitation events is of critical importance to preparing for and adapting to climate change. Making accurat…
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Jaideep Pathak, Shashank Subramanian, Peter Harrington +10
FourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.2…
Ensemble inversion for brain tumor growth models with mass effect
Shashank Subramanian, Klaudius Scheufele, Naveen Himthani +2
We propose a method for extracting physics-based biomarkers from a single multiparametric Magnetic Resonance Imaging (mpMRI) scan bearing a glioma tumor. We account for mass effect…
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett +6
Current clinical decision-making in oncology relies on averages of large patient populations to both assess tumor status and treatment outcomes. However, cancers exhibit an inheren…
Calibration of Biophysical Models for tau-Protein Spreading in Alzheimer's Disease from PET-MRI
Klaudius Scheufele, Shashank Subramanian, George Biros
Aggregates of misfolded tau proteins (or just 'tau' for brevity) play a crucial role in the progression of Alzheimer's disease (AD) as they correlate with cell death and accelerate…
Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect
Shashank Subramanian, Klaudius Scheufele, Naveen Himthani +1
We present a 3D fully-automatic method for the calibration of partial differential equation (PDE) models of glioblastoma (GBM) growth with mass effect, the deformation of brain tis…