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Peter Harrington
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2020 – today
- 2024
- [i17]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 abs/2401.15305 (2024) - [i16]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 abs/2404.19630 (2024) - [i15]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:
Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators. CoRR abs/2408.01581 (2024) - [i14]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:
Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators. CoRR abs/2408.03100 (2024) - [i13]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:
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. CoRR abs/2408.10958 (2024) - [i12]Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji:
Comprehensive Performance Modeling and System Design Insights for Foundation Models. CoRR abs/2410.00273 (2024) - 2023
- [j4]Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown:
Towards Stability of Autoregressive Neural Operators. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Ching-Lun Tai, Peter Harrington:
Efficient Segment-Level Waveform Anomaly Detection for Memory Devices. ICC 2023: 3376-3381 - [c5]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 - [c4]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: 13:1-13:11 - [i11]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. CoRR abs/2306.00258 (2023) - [i10]Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown:
Towards Stability of Autoregressive Neural Operators. CoRR abs/2306.10619 (2023) - 2022
- [i9]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 abs/2202.11214 (2022) - [i8]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 abs/2208.05419 (2022) - [i7]James Duncan, Shashank Subramanian, Peter Harrington:
Generative Modeling of High-resolution Global Precipitation Forecasts. CoRR abs/2210.12504 (2022) - 2021
- [j3]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:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [j2]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): 1641-1652 (2021) - [i6]Md. Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa:
Estimating Galactic Distances From Images Using Self-supervised Representation Learning. CoRR abs/2101.04293 (2021) - [i5]Peter Harrington, Mustafa Mustafa, Max Dornfest, Benjamin Horowitz, Zarija Lukic:
Fast, high-fidelity Lyman α forests with convolutional neural networks. CoRR abs/2106.12662 (2021) - [i4]George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic:
Mining for strong gravitational lenses with self-supervised learning. CoRR abs/2110.00023 (2021) - [i3]George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic:
Self-supervised similarity search for large scientific datasets. CoRR abs/2110.13151 (2021) - 2020
- [j1]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): 2232 (2020) - [c3]Peter Harrington, Wai Pang Ng, Richard Binns:
Autonomous drone control within a Wi-Fi network. CSNDSP 2020: 1-6 - [i2]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 abs/2007.12856 (2020) - [i1]Md. Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa:
Self-Supervised Representation Learning for Astronomical Images. CoRR abs/2012.13083 (2020)
2010 – 2019
- 2019
- [b1]Peter Harrington:
Autonomous drone network: non-intrusive control and indoor formation positioning. Northumbria University, Newcastle upon Tyne, UK, 2019 - 2018
- [c2]Tianrong 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: 1-4 - [c1]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: 1-6
Coauthor Index
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last updated on 2024-11-06 21:34 CET by the dblp team
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