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Mark S. Neubauer
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- affiliation: University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, IL, USA
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2020 – today
- 2024
- [j8]Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo
, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Shen Wang, Thomas K. Warburton:
Corrigendum: Applications and techniques for fast machine learning in science. Frontiers Big Data 6 (2024) - 2023
- [j7]Wahid Bhimji, Dale Carder, Eli Dart
Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access. Comput. Softw. Big Sci. 7(1): 5 (2023) - [j6]Ayush Khot
A detailed study of interpretability of deep neural network based top taggers. Mach. Learn. Sci. Technol. 4(3): 35003 (2023) - [j5]Javier M. Duarte
FAIR AI models in high energy physics. Mach. Learn. Sci. Technol. 4(4): 45062 (2023) - [c2]Shi-Yu Huang, Yun-Chen Yang, Yu-Ru Su, Bo-Cheng Lai, Javier M. Duarte
Low Latency Edge Classification GNN for Particle Trajectory Tracking on FPGAs. FPL 2023: 294-298 - [i22]Shi-Yu Huang, Yun-Chen Yang, Yu-Ru Su, Bo-Cheng Lai, Javier M. Duarte, Scott Hauck, Shih-Chieh Hsu, Jin-Xuan Hu, Mark S. Neubauer:
Low Latency Edge Classification GNN for Particle Trajectory Tracking on FPGAs. CoRR abs/2306.11330 (2023) - 2022
- [j4]Allison McCarn Deiana, Nhan Tran
Applications and Techniques for Fast Machine Learning in Science. Frontiers Big Data 5: 787421 (2022) - [j3]Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier M. Duarte
Graph Neural Networks for Charged Particle Tracking on FPGAs. Frontiers Big Data 5: 828666 (2022) - [i21]Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier M. Duarte, Sanmay Ganguly, Michael Kagan
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges. CoRR abs/2203.12852 (2022) - [i20]Philip C. Harris, Erik Katsavounidis, William Patrick McCormack, Dylan S. Rankin
Physics Community Needs, Tools, and Resources for Machine Learning. CoRR abs/2203.16255 (2022) - [i19]Mark S. Neubauer, Avik Roy:
Explainable AI for High Energy Physics. CoRR abs/2206.06632 (2022) - [i18]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) - [i17]W. Bhimij, Dale Carder
Snowmass 2021 Computational Frontier CompF4 Topical Group Report: Storage and Processing Resource Access. CoRR abs/2209.08868 (2022) - [i16]Ayush Khot, Mark S. Neubauer, Avik Roy:
A Detailed Study of Interpretability of Deep Neural Network based Top Taggers. CoRR abs/2210.04371 (2022) - [i15]Eliu A. Huerta, Ben Blaiszik, L. Catherine Brinson, Kristofer E. Bouchard, Daniel Diaz, Caterina Doglioni, Javier M. Duarte, Murali Emani, Ian T. Foster, Geoffrey C. Fox, Philip C. Harris, Lukas Heinrich, Shantenu Jha
FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. CoRR abs/2210.08973 (2022) - [i14]Javier M. Duarte, Haoyang Li, Avik Roy, Ruike Zhu, Eliu A. Huerta, Daniel Diaz, Philip C. Harris, Raghav Kansal, Daniel S. Katz, Ishaan H. Kavoori, Volodymyr V. Kindratenko, Farouk Mokhtar, Mark S. Neubauer, Sang Eon Park, Melissa Quinnan, Roger Rusack, Zhizhen Zhao:
FAIR AI Models in High Energy Physics. CoRR abs/2212.05081 (2022) - 2021
- [j2]Gage DeZoort
Charged Particle Tracking via Edge-Classifying Interaction Networks. Comput. Softw. Big Sci. 5(1) (2021) - [i13]Xiangyang Ju
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. CoRR abs/2103.06995 (2021) - [i12]Gage DeZoort
Charged particle tracking via edge-classifying interaction networks. CoRR abs/2103.16701 (2021) - [i11]Yifan Chen, Eliu A. Huerta, Javier M. Duarte
A FAIR and AI-ready Higgs Boson Decay Dataset. CoRR abs/2108.02214 (2021) - [i10]Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021) - [i9]Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier M. Duarte
Graph Neural Networks for Charged Particle Tracking on FPGAs. CoRR abs/2112.02048 (2021) - 2020
- [i8]Robert W. Gardner, Lincoln Bryant, Mark S. Neubauer, Frank Würthwein, Judith Stephen, Andrew A. Chien:
The Scalable Systems Laboratory: a Platform for Software Innovation for HEP. CoRR abs/2005.06151 (2020) - [i7]Daniel S. Katz, Sudhir Malik
Software Sustainability & High Energy Physics. CoRR abs/2010.05102 (2020) - [i6]Aneesh Heintz, Vesal Razavimaleki, Javier M. Duarte
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs. CoRR abs/2012.01563 (2020)
2010 – 2019
- 2019
- [j1]Eliu A. Huerta
Supporting High-Performance and High-Throughput Computing for Experimental Science. Comput. Softw. Big Sci. 3(1) (2019) - [i5]Gabrielle Allen, Igor Andreoni, Etienne Bachelet
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era. CoRR abs/1902.00522 (2019) - [i4]Eliu A. Huerta, Gabrielle Allen, Igor Andreoni, Javier Mauricio Antelis, Etienne Bachelet
Enabling real-time multi-messenger astrophysics discoveries with deep learning. CoRR abs/1911.11779 (2019) - 2018
- [c1]Maxim Belkin, Roland Haas
Container solutions for HPC Systems: A Case Study of Using Shifter on Blue Waters. PEARC 2018: 43:1-43:8 - [i3]Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano
Machine Learning in High Energy Physics Community White Paper. CoRR abs/1807.02876 (2018) - [i2]Maxim Belkin, Roland Haas
Container solutions for HPC Systems: A Case Study of Using Shifter on Blue Waters. CoRR abs/1808.00556 (2018) - [i1]Eliu A. Huerta, Roland Haas
Supporting High-Performance and High-Throughput Computing for Experimental Science. CoRR abs/1810.03056 (2018)
Coauthor Index
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last updated on 2024-11-04 20:44 CET by the dblp team
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