Publications (27)
Comprehensive Performance Modeling and System Design Insights for Foundation Models
Shashank Subramanian, Ermal Rrapaj, Peter Harrington +6
Where did the tumor start? An inverse solver with sparse localization for tumor growth models
Shashank Subramanian, Klaudius Scheufele, Miriam Mehl +1
Automatic MRI-Driven Model Calibration for Advanced Brain Tumor Progression Analysis
Klaudius Scheufele, Shashank Subramanian, George Biros
Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect
Shashank Subramanian, Klaudius Scheufele, Naveen Himthani +1
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
A Novel Domain Adaptation Framework for Medical Image Segmentation
Amir Gholami, Shashank Subramanian, Varun Shenoy +6
Anomalous Diffusion of Tropical Cyclones Observed in Huge Ensembles of Hindcasts
Abdoul R. Zeba, William D. Collins, Ankur Mahesh +5
Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators
Ankur Mahesh, William Collins, Boris Bonev +13
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning
Pu Ren, N. Benjamin Erichson, Junyi Guo +4
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney +1
Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect
Shashank Subramanian, Amir Gholami, George Biros
Surface temperature extremes produced by huge machine learning hindcasts of summer 2023
Mark Risser, Ankur Mahesh, Joshua North +6
Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators
Ankur Mahesh, William Collins, Boris Bonev +12
Towards Stability of Autoregressive Neural Operators
Michael McCabe, Peter Harrington, Shashank Subramanian +1
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators
Thorsten Kurth, Shashank Subramanian, Peter Harrington +6
Calibration of Biophysical Models for tau-Protein Spreading in Alzheimer's Disease from PET-MRI
Klaudius Scheufele, Shashank Subramanian, George Biros
On Neural Scaling Laws for Weather Emulation through Continual Training
Shashank Subramanian, Alexander Kiefer, Arnur Nigmetov +3
Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction
Jared D. Willard, Peter Harrington, Shashank Subramanian +3
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Shashank Subramanian, Peter Harrington, Kurt Keutzer +4
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Jaideep Pathak, Shashank Subramanian, Peter Harrington +10
Generative Modeling of High-resolution Global Precipitation Forecasts
James Duncan, Shashank Subramanian, Peter Harrington
Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology
Andreas Mang, Spyridon Bakas, Shashank Subramanian +2
Ensemble inversion for brain tumor growth models with mass effect
Shashank Subramanian, Klaudius Scheufele, Naveen Himthani +2
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning
Wuyang Chen, Jialin Song, Pu Ren +3
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett +6
Image-Driven Biophysical Tumor Growth Model Calibration
Klaudius Scheufele, Shashank Subramanian, Andreas Mang +2
Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators
Ankur Mahesh, William D. Collins, Travis A. O'Brien +10