Peter Harrington

32 papers A* 1Journal 24Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting. CoRR Jean Kossaifi, Nikola B. Kovachki, Morteza Mardani, Daniel V. Leibovici, Suman Ravuri, Ira Shokar, Edoardo Calvello, Mohammad Shoaib Abbas, Peter Harrington, Ashay Subramaniam, Noah D. Brenowitz, Boris Bonev, Wonmin Byeon, Karsten Kreis, Dale R. Durran, Arash Vahdat, Mike Pritchard, Jan Kautz
2025	J	`jnl`	MoWE : A Mixture of Weather Experts. CoRR Dibyajyoti Chakraborty, Romit Maulik, Peter Harrington, Dallas Foster, Mohammad Amin Nabian, Sanjay Choudhry
2024	J	`jnl`	A Practical Probabilistic Benchmark for AI Weather Models. CoRR Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Ankur Mahesh, Boris Bonev, Thorsten Kurth, Dale R. Durran, Peter Harrington, Michael S. Pritchard
2024	J	`jnl`	Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction. CoRR Jared D. Willard, Peter Harrington, Shashank Subramanian, Ankur Mahesh, Travis A. O'Brien, William D. Collins
2024	—	`conf`	Comprehensive Performance Modeling and System Design Insights for Foundation Models. SC Workshops Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji
2024	J	`jnl`	Comprehensive Performance Modeling and System Design Insights for Foundation Models. CoRR Shashank Subramanian, Ermal Rrapaj, Peter Harrington, Smeet Chheda, Steven Farrell, Brian Austin, Samuel Williams, Nicholas J. Wright, Wahid Bhimji
2024	J	`jnl`	Hierarchical Conditional Multi-Task Learning for Streamflow Modeling. CoRR Shaoming Xu, Arvind Renganathan, Ankush Khandelwal, Rahul Ghosh, Xiang Li, Licheng Liu, Kshitij Tayal, Peter Harrington, Xiaowei Jia, Zhenong Jin, John Nieber, Vipin Kumar
2024	J	`jnl`	Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators. CoRR 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
2024	J	`jnl`	Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators. CoRR 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
2024	J	`jnl`	Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. CoRR 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
2023	—	`conf`	Efficient Segment-Level Waveform Anomaly Detection for Memory Devices. ICC Ching-Lun Tai, Peter Harrington
2023	—	`conf`	FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. PASC Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Anima Anandkumar
2023	A*	`conf`	Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. NeurIPS Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami
2023	J	`jnl`	Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior. CoRR Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami
2023	J	`jnl`	Towards Stability of Autoregressive Neural Operators. CoRR Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown
2023	J	`jnl`	Towards Stability of Autoregressive Neural Operators. Trans. Mach. Learn. Res. Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown
2022	J	`jnl`	FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR 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
2022	J	`jnl`	FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators. CoRR Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Animashree Anandkumar
2022	J	`jnl`	Generative Modeling of High-resolution Global Precipitation Forecasts. CoRR James Duncan, Shashank Subramanian, Peter Harrington
2021	J	`jnl`	Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 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 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
2021	J	`jnl`	Estimating Galactic Distances From Images Using Self-supervised Representation Learning. CoRR Md. Abul Hayat, Peter Harrington, George Stein, Zarija Lukic, Mustafa Mustafa
2021	J	`jnl`	Fast, high-fidelity Lyman α forests with convolutional neural networks. CoRR Peter Harrington, Mustafa Mustafa, Max Dornfest, Benjamin Horowitz, Zarija Lukic
2021	J	`jnl`	Mining for strong gravitational lenses with self-supervised learning. CoRR George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan, Zarija Lukic
2021	J	`jnl`	Self-supervised similarity search for large scientific datasets. CoRR George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic
2021	J	`jnl`	The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism. IEEE Trans. Parallel Distributed Syst. Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
2020	—	`conf`	Autonomous drone control within a Wi-Fi network. CSNDSP Peter Harrington, Wai Pang Ng, Richard Binns
2020	J	`jnl`	Integrating Radio-Over-Fiber Communication System and BOTDR Sensor System. Sensors Wai Pang Ng, Nageswara Lalam, Xuewu Dai, Qiang Wu, Yong Qing Fu, Peter Harrington, Nathan J. Gomes, Chao Lu
2020	J	`jnl`	Self-Supervised Representation Learning for Astronomical Images. CoRR Md. Abul Hayat, George Stein, Peter Harrington, Zarija Lukic, Mustafa Mustafa
2020	J	`jnl`	The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism. CoRR Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, Brian Van Essen
2019	—	`—`	Autonomous drone network: non-intrusive control and indoor formation positioning. Peter Harrington
2018	—	`conf`	Establishing the flightpath of a quadcopter drone from the relative angular velocity of the four rotors. CSNDSP Peter Harrington, Tianrong Chen, Wai Pang Ng
2018	—	`conf`	Multi point strain and temperature sensing based on Brillouin optical time domain reflectometry. CSNDSP Tianrong Chen, X. Xu, Nageswara Lalam, Wai Pang Ng, Peter Harrington