Peter Harrington

According to our database, Peter Harrington authored at least 25 papers between 2018 and 2024.

Collaborative distances:

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

2024

Hierarchical Conditional Multi-Task Learning for Streamflow Modeling.

Shaoming Xu, Arvind Renganathan, Ankush Khandelwal, Rahul Ghosh, Xiang Li, Licheng Liu, Kshitij Tayal, Peter Harrington, Xiaowei Jia, Zhenong Jin, John Nieber, Vipin Kumar

CoRR, 2024

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling.

Jaideep Pathak, Yair Cohen, Piyush Garg, Peter Harrington, Noah D. Brenowitz, Dale R. Durran, Morteza Mardani, Arash Vahdat, Shaoming Xu, Karthik Kashinath, Michael S. Pritchard

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, 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

Comprehensive Performance Modeling and System Design Insights for Foundation Models.

Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

2023

Towards Stability of Autoregressive Neural Operators.

Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown

Trans. Mach. Learn. Res., 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

Proceedings of the Platform for Advanced Scientific Computing Conference, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Segment-Level Waveform Anomaly Detection for Memory Devices.

Ching-Lun Tai, Peter Harrington

Proceedings of the IEEE International Conference on Communications, 2023

2022

Generative Modeling of High-resolution Global Precipitation Forecasts.

James Duncan, Shashank Subramanian, Peter Harrington

CoRR, 2022

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, Animashree Anandkumar

CoRR, 2022

2021

The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism.

Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen

IEEE Trans. Parallel Distributed Syst., 2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).

Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon

Int. J. High Perform. Comput. Appl., 2021

Self-supervised similarity search for large scientific datasets.

George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic

CoRR, 2021

Mining for strong gravitational lenses with self-supervised learning.

George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic

CoRR, 2021

Fast, high-fidelity Lyman α forests with convolutional neural networks.

Peter Harrington, Mustafa Mustafa, Max Dornfest, Benjamin Horowitz, Zarija Lukic

CoRR, 2021

Estimating Galactic Distances From Images Using Self-supervised Representation Learning.

Md. Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa

CoRR, 2021

2020

Integrating Radio-Over-Fiber Communication System and BOTDR Sensor System.

Wai Pang Ng, Nageswara Lalam, Xuewu Dai, Qiang Wu, Yong Qing Fu, Peter Harrington, Nathan J. Gomes, Chao Lu

Sensors, 2020

Self-Supervised Representation Learning for Astronomical Images.

Md. Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa

CoRR, 2020

Autonomous drone control within a Wi-Fi network.

Peter Harrington, Wai Pang Ng, Richard Binns

Proceedings of the 12th International Symposium on Communication Systems, 2020

2019

Autonomous drone network: non-intrusive control and indoor formation positioning.

Peter Harrington

PhD thesis, 2019

2018

Establishing the flightpath of a quadcopter drone from the relative angular velocity of the four rotors.

Peter Harrington, Tianrong Chen, Wai Pang Ng

Proceedings of the 11th International Symposium on Communication Systems, 2018

Multi point strain and temperature sensing based on Brillouin optical time domain reflectometry.

Tianrong Chen, X. Xu, Nageswara Lalam, Wai Pang Ng, Peter Harrington

Proceedings of the 11th International Symposium on Communication Systems, 2018