A Novel Domain Adaptation Framework for Medical Image Segmentation. - Amir Gholami; Shashank Subramanian; Varun Shenoy; Naveen Himthani; Xiangyu Yue 001; Sicheng Zhao; Peter H. Jin; George Biros; Kurt Keutzer (BrainLes@MICCAI (2), 2018)

Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression. - Sarthak Pati; Vaibhav Sharma; Heena Aslam; Siddhesh P. Thakur; Hamed Akbari; Andreas Mang; Shashank Subramanian; George Biros; Christos Davatzikos; Spyridon Bakas (BrainLes@MICCAI (1), 2020)

Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect. - Shashank Subramanian; Klaudius Scheufele; Naveen Himthani; George Biros (MICCAI (2), 2020)

Image-Driven Biophysical Tumor Growth Model Calibration. - Klaudius Scheufele; Shashank Subramanian; Andreas Mang; George Biros; Miriam Mehl (SIAM J. Sci. Comput., 2020)

Quantitative in vivo imaging to enable tumor forecasting and treatment optimization. - Guillermo Lorenzo; David A. Hormuth II; Angela M. Jarrett; Ernesto A. B. F. Lima; Shashank Subramanian; George Biros; J. Tinsley Oden; Thomas J. R. Hughes; Thomas E. Yankeelov (CoRR, 2021)

Ensemble inversion for brain tumor growth models with mass effect. - Shashank Subramanian; Klaudius Scheufele; Naveen Himthani; Christos Davatzikos; George Biros (CoRR, 2021)

Fully Automatic Calibration of Tumor-Growth Models Using a Single mpMRI Scan. - Klaudius Scheufele; Shashank Subramanian; George Biros (IEEE Trans. Medical Imaging, 2021)

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. - Jaideep Pathak; Shashank Subramanian; Peter Harrington; Sanjeev Raja; Ashesh Chattopadhyay; Morteza Mardani; Thorsten Kurth; David Hall; Zongyi Li; Kamyar Azizzadenesheli; Pedram Hassanzadeh; Karthik Kashinath; et al. (CoRR, 2022)

Generative Modeling of High-resolution Global Precipitation Forecasts. - James Duncan 002; Shashank Subramanian; Peter Harrington (CoRR, 2022)

Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. - Shashank Subramanian; Robert M. Kirby; Michael W. Mahoney; Amir Gholami (ECAI, 2023)

Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. - Shashank Subramanian; Peter Harrington; Kurt Keutzer; Wahid Bhimji; Dmitriy Morozov; Michael W. Mahoney; Amir Gholami (NeurIPS, 2023)

FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. - Thorsten Kurth; Shashank Subramanian; Peter Harrington; Jaideep Pathak; Morteza Mardani; David Hall; Andrea Miele; Karthik Kashinath; Anima Anandkumar (PASC, 2023)

SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning. - Pu Ren; N. Benjamin Erichson; Shashank Subramanian; Omer San; Zarija Lukic; Michael W. Mahoney (CoRR, 2023)

Towards Stability of Autoregressive Neural Operators. - Michael McCabe; Peter Harrington; Shashank Subramanian; Jed Brown (Trans. Mach. Learn. Res., 2023)

Ensemble Inversion for Brain Tumor Growth Models With Mass Effect. - Shashank Subramanian; Ali Ghafouri; Klaudius Matthias Scheufele; Naveen Himthani; Christos Davatzikos; George Biros (IEEE Trans. Medical Imaging, 2023)

Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning. - Wuyang Chen 001; Jialin Song; Pu Ren; Shashank Subramanian; Dmitriy Morozov; Michael W. Mahoney (NeurIPS, 2024)

Comprehensive Performance Modeling and System Design Insights for Foundation Models. - Shashank Subramanian; Ermal Rrapaj; Peter Harrington; Smeet Chheda; Steven Farrell; Brian Austin; Samuel Williams 001; Nicholas J. Wright; Wahid Bhimji (SC Workshops, 2024)

Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction. - Jared D. Willard; Peter Harrington; Shashank Subramanian; Ankur Mahesh; Travis A. O'Brien; William D. Collins (CoRR, 2024)

Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators. - Ankur Mahesh; William D. Collins; Boris Bonev; Noah D. Brenowitz; Yair Cohen; Peter Harrington; Karthik Kashinath; Thorsten Kurth; Joshua North; Travis A. O'Brien; Michael S. Pritchard; David Pruitt; et al. (CoRR, 2024)

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators. - Ankur Mahesh; William D. Collins; Boris Bonev; Noah D. Brenowitz; Yair Cohen; Joshua Elms; Peter Harrington; Karthik Kashinath; Thorsten Kurth; Joshua North; Travis A. O'Brien; Michael S. Pritchard; et al. (CoRR, 2024)