Peter Harrington

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 23

Top Topics

Weather Forecasting

Angular Velocity

Convolutional Neural Networks

Top Venues

Publications

Jared D. Willard, Peter Harrington, Shashank Subramanian, Ankur Mahesh, Travis A. O'Brien, William D. Collins
Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction. CoRR (2024)
Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Ankur Mahesh, Boris Bonev, Thorsten Kurth, Dale R. Durran, Peter Harrington, Michael S. Pritchard
A Practical Probabilistic Benchmark for AI Weather Models. CoRR (2024)
Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown
Towards Stability of Autoregressive Neural Operators. CoRR (2023)
Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael Mahoney, Amir Gholami
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. CoRR (2023)
Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. NeurIPS (2023)
Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown
Towards Stability of Autoregressive Neural Operators. Trans. Mach. Learn. Res. 2023 (2023)
Ching-Lun Tai, Peter Harrington
Efficient Segment-Level Waveform Anomaly Detection for Memory Devices. ICC (2023)
Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Anima Anandkumar
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. PASC (2023)
James Duncan, Shashank Subramanian, Peter Harrington
Generative Modeling of High-resolution Global Precipitation Forecasts. CoRR (2022)
Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Animashree Anandkumar
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators. CoRR (2022)
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
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR (2022)
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism. IEEE Trans. Parallel Distributed Syst. 32 (7) (2021)
George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic
Self-supervised similarity search for large scientific datasets. CoRR (2021)
Md Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa
Estimating Galactic Distances From Images Using Self-supervised Representation Learning. CoRR (2021)
Francis J. Alexander, James 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 Ramakrishniah, 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
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35 (6) (2021)
George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic
Mining for strong gravitational lenses with self-supervised learning. CoRR (2021)
Peter Harrington, Mustafa Mustafa, Max Dornfest, Benjamin Horowitz, Zarija Lukic
Fast, high-fidelity Lyman α forests with convolutional neural networks. CoRR (2021)
Wai Pang Ng, Nageswara Lalam, Xuewu Dai, Qiang Wu, Yong Qing Fu, Peter Harrington, Nathan J. Gomes, Chao Lu
Integrating Radio-Over-Fiber Communication System and BOTDR Sensor System. Sensors 20 (8) (2020)
Md Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa
Self-Supervised Representation Learning for Astronomical Images. CoRR (2020)
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism. CoRR (2020)
Peter Harrington, Wai Pang Ng, Richard Binns
Autonomous drone control within a Wi-Fi network. CSNDSP (2020)
T. Chen, X. Xu, Nageswara Lalam, Wai Pang Ng, Peter Harrington
Multi point strain and temperature sensing based on Brillouin optical time domain reflectometry. CSNDSP (2018)
Peter Harrington, Tianrong Chen, Wai Pang Ng
Establishing the flightpath of a quadcopter drone from the relative angular velocity of the four rotors. CSNDSP (2018)