Ankur Mahesh

According to our database, Ankur Mahesh authored at least 6 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale.

Boris Bonev, Thorsten Kurth, Ankur Mahesh, Mauro Bisson, Jean Kossaifi, Karthik Kashinath, Anima Anandkumar, William D. Collins, Michael S. Pritchard, Alexander Keller

CoRR, July, 2025

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, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard

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, Mark Risser, Shashank Subramanian, Jared Willard

CoRR, 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

A Practical Probabilistic Benchmark for AI Weather Models.

Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Ankur Mahesh, Boris Bonev, Thorsten Kurth, Dale R. Durran, Peter Harrington, Michael S. Pritchard

CoRR, 2024

2018

Exascale deep learning for climate analytics.

Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston

Proceedings of the International Conference for High Performance Computing, 2018