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ORCIDKazuhiro Terao
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2020 – today
- 2024
[j2]Sean Gasiorowski
, Yifan Chen, Youssef S. G. Nashed, Pierre Granger, Camelia Mironov, Ka Vang Tsang, Daniel Ratner, Kazuhiro Terao:
Differentiable simulation of a liquid argon time projection chamber. Mach. Learn. Sci. Technol. 5(2): 25012 (2024)- 2022
- [b1]Paolo Calafiura, David Rousseau, Kazuhiro Terao:
Artificial Intelligence for High Energy Physics. WorldScientific 2022, ISBN 9789811234026, pp. 1-828 - [i11]Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier M. Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao:
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges. CoRR abs/2203.12852 (2022) - [i10]Gabriele Benelli, Thomas Y. Chen, Javier M. Duarte, Matthew Feickert, Matthew J. Graham, Lindsey Gray, Dan Hackett, Philip C. Harris, Shih-Chieh Hsu, Gregor Kasieczka, Elham E Khoda, Matthias Komm, Mia Liu, Mark S. Neubauer, Scarlet Norberg, Alexx Perloff, Marcel Rieger, Claire Savard, Kazuhiro Terao, Savannah Thais, Avik Roy, Jean-Roch Vlimant, Grigorios Chachamis:
Data Science and Machine Learning in Education. CoRR abs/2207.09060 (2022) - [i9]Phiala E. Shanahan, Kazuhiro Terao, Daniel Whiteson:
Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning. CoRR abs/2209.07559 (2022) - [i8]Minjie Lei, Ka Vang Tsang, Sean Gasiorowski, Chuan Li, Youssef S. G. Nashed, Gianluca Petrillo, Olivia Piazza, Daniel Ratner, Kazuhiro Terao:
Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector. CoRR abs/2211.01505 (2022) - 2021
- [i7]François Drielsma, Kazuhiro Terao, Laura Dominé, Dae Heun Koh:
Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors. CoRR abs/2102.01033 (2021) - 2020
- [i6]Corey Adams, Kazuhiro Terao, Taritree Wongjirad:
PILArNet: Public Dataset for Particle Imaging Liquid Argon Detectors in High Energy Physics. CoRR abs/2006.01993 (2020) - [i5]Laura Dominé, Kazuhiro Terao:
Point Proposal Network for Reconstructing 3D Particle Positions with Sub-Pixel Precision in Liquid Argon Time Projection Chambers. CoRR abs/2006.14745 (2020) - [i4]Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy L. Usher:
Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR abs/2007.00149 (2020) - [i3]François Drielsma, Qing Lin, Pierre Côte de Soux, Laura Dominé, Ran Itay, Dae Heun Koh, Bradley J. Nelson, Kazuhiro Terao, Ka Vang Tsang, Tracy L. Usher:
Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data. CoRR abs/2007.01335 (2020) - [i2]Dae Heun Koh, Pierre Côte de Soux, Laura Dominé, François Drielsma, Ran Itay, Qing Lin, Kazuhiro Terao, Ka Vang Tsang, Tracy L. Usher:
Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers. CoRR abs/2007.03083 (2020)
2010 – 2019
- 2019
- [i1]Laura Dominé, Kazuhiro Terao:
Scalable Deep Convolutional Neural Networks for Sparse, Locally Dense Liquid Argon Time Projection Chamber Data. CoRR abs/1903.05663 (2019) - 2018
- [j1]Alexander Radovic, Mike Williams, David Rousseau, Michael Kagan, Daniele Bonacorsi, Alexander Himmel, Adam Aurisano, Kazuhiro Terao, Taritree Wongjirad:
Machine learning at the energy and intensity frontiers of particle physics. Nat. 560(7716): 41-48 (2018)
Coauthor Index
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