Shih-Chieh Hsu

According to our database, Shih-Chieh Hsu authored at least 32 papers between 1993 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation.

Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang

CoRR, 2024

FAIR Universe HiggsML Uncertainty Challenge Competition.

Wahid Bhimji, Paolo Calafiura, Ragansu Chakkappai, Yuan-Tang Chou, Sascha Diefenbacher, Jordan Dudley, Steven Farrell, Aishik Ghosh, Isabelle Guyon, Chris Harris, Shih-Chieh Hsu, Elham E Khoda, Rémy Lyscar, Alexandre Michon, Benjamin Nachman, Peter Nugent, Mathis Reymond, David Rousseau, Benjamin Sluijter, Benjamin Thorne, Ihsan Ullah, Yulei Zhang

CoRR, 2024

Low Latency Transformer Inference on FPGAs for Physics Applications with hls4ml.

Zhixing Jiang, Dennis Yin, Yihui Chen, Elham E Khoda, Scott Hauck, Shih-Chieh Hsu, Ekaterina Govorkova, Philip C. Harris, Vladimir Loncar, Eric A. Moreno

CoRR, 2024

Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation.

Qibin Liu, Chase Shimmin, Xiulong Liu, Eli Shlizerman, Shu Li, Shih-Chieh Hsu

CoRR, 2024

FPGA Deployment of LFADS for Real-time Neuroscience Experiments.

Xiaohan Liu, ChiJui Chen, YanLun Huang, LingChi Yang, Elham E Khoda, Yihui Chen, Scott Hauck, Shih-Chieh Hsu, Bo-Cheng Lai

CoRR, 2024

Ultra Fast Transformers on FPGAs for Particle Physics Experiments.

Zhixing Jiang, Dennis Yin, Elham E Khoda, Vladimir Loncar, Ekaterina Govorkova, Eric A. Moreno, Philip C. Harris, Scott Hauck, Shih-Chieh Hsu

CoRR, 2024

Deep-Learning Based Classification of Clinical Significance for Prostate Cancer.

Jia-Hao Chen, Shih-Chieh Hsu, Chih-Yu Shen, Gia-Shing Shieh, Chun-Hung Yang, Yung-Ming Kuo

Proceedings of the International Conference on Consumer Electronics - Taiwan, 2024

2023

Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml.

Elham E Khoda, Dylan S. Rankin, Rafael Teixeira de Lima, Philip C. Harris, Scott Hauck, Shih-Chieh Hsu, Michael Kagan, Vladimir Loncar, Chaitanya Paikara, Richa Rao, Sioni Summers, Caterina Vernieri, Aaron Wang

Mach. Learn. Sci. Technol., June, 2023

Extended Symmetry Preserving Attention Networks for LHC Analysis.

Michael James Fenton, Alexander Shmakov, Hideki Okawa, Yuji Li, Ko-Yang Hsiao, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi

CoRR, 2023

Low Latency Edge Classification GNN for Particle Trajectory Tracking on FPGAs.

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

Proceedings of the 33rd International Conference on Field-Programmable Logic and Applications, 2023

2022

Quantum Machine Learning with SQUID.

Alessandro Roggero, Jakub Filipek, Shih-Chieh Hsu, Nathan Wiebe

Quantum, 2022

Graph Neural Networks for Charged Particle Tracking on FPGAs.

Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier M. Duarte, Markus Atkinson, Gage DeZoort, Peter Elmer, Scott Hauck, Jin-Xuan Hu, Shih-Chieh Hsu, Bo-Cheng Lai, Mark S. Neubauer, Isobel Ojalvo, Savannah Thais, Matthew Trahms

Frontiers Big Data, 2022

Data Science and Machine Learning in Education.

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

CoRR, 2022

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark.

Hendrik Borras, Giuseppe Di Guglielmo, Javier M. Duarte, Nicolò Ghielmetti, Benjamin Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott

CoRR, 2022

QONNX: Representing Arbitrary-Precision Quantized Neural Networks.

Alessandro Pappalardo, Yaman Umuroglu, Michaela Blott, Jovan Mitrevski, Benjamin Hawks, Nhan Tran, Vladimir Loncar, Sioni Summers, Hendrik Borras, Jules Muhizi, Matthew Trahms, Shih-Chieh Hsu, Scott Hauck, Javier M. Duarte

CoRR, 2022

Exploring the Universality of Hadronic Jet Classification.

Kingman Cheung, Yi-Lun Chung, Shih-Chieh Hsu, Benjamin Nachman

CoRR, 2022

Physics Community Needs, Tools, and Resources for Machine Learning.

Philip C. Harris, Erik Katsavounidis, William Patrick McCormack, Dylan S. Rankin, Yongbin Feng, Abhijith Gandrakota, Christian Herwig, Burt Holzman, Kevin Pedro, Nhan Tran, Tingjun Yang, Jennifer Ngadiuba, Michael Coughlin, Scott Hauck, Shih-Chieh Hsu, Elham E Khoda, Deming Chen, Mark S. Neubauer, Javier M. Duarte, Georgia Karagiorgi, Mia Liu

CoRR, 2022

Anthropomorphism of AI-based Intelligent Customer Service, and Its Affective and Behavioral Consequences.

Yu-Ting Chang-Chien, Jacob Chun Cheng, Shih-Chieh Hsu, Yi Wen Yeh

Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

2021

GPU coprocessors as a service for deep learning inference in high energy physics.

Jeffrey D. Krupa, Kelvin Lin, Maria Acosta Flechas, Jack Dinsmore, Javier M. Duarte, Philip C. Harris, Scott Hauck, Burt Holzman, Shih-Chieh Hsu, Thomas Klijnsma, Mia Liu, Kevin Pedro, Dylan S. Rankin, Natchanon Suaysom, Matt Trahms, Nhan Tran

Mach. Learn. Sci. Technol., 2021

Graph Neural Networks for Charged Particle Tracking on FPGAs.

Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier M. Duarte, Markus Atkinson, Gage DeZoort, Peter Elmer, Jin-Xuan Hu, Shih-Chieh Hsu, Bo-Cheng Lai, Mark S. Neubauer, Isobel Ojalvo, Savannah Thais

CoRR, 2021

Applications and Techniques for Fast Machine Learning in Science.

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, 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, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

CoRR, 2021

SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention.

Alexander Shmakov, Michael James Fenton, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi

CoRR, 2021

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline.

Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Nicholas Choma, Sean Conlon, Steven Farrell, Yaoyuan Xu, Maria Spiropulu, Jean-Roch Vlimant, Adam Aurisano, Jeremy Hewes, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Markus Atkinson, Mark S. Neubauer, Gage DeZoort, Savannah Thais, Aditi Chauhan, Alex Schuy, Shih-Chieh Hsu, Alexandra Ballow, Alina Lazar

CoRR, 2021

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices.

Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P. Carloni, Giuseppe Di Guglielmo, Philip C. Harris, Jeffrey D. Krupa, Dylan S. Rankin, Manuel Blanco Valentin, Josiah D. Hester, Yingyi Luo, John Mamish, Seda Ogrenci Memik, Thea Aarrestad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier M. Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, Zhenbin Wu

CoRR, 2021

2020

Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networks.

Michael James Fenton, Alexander Shmakov, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi

CoRR, 2020

GPU coprocessors as a service for deep learning inference in high energy physics.

Jeffrey D. Krupa, Kelvin Lin, Maria Acosta Flechas, Jack Dinsmore, Javier M. Duarte, Philip C. Harris, Scott Hauck, Burt Holzman, Shih-Chieh Hsu, Thomas Klijnsma, Mia Liu, Kevin Pedro, Natchanon Suaysom, Matt Trahms, Nhan Tran

CoRR, 2020

FPGAs-as-a-Service Toolkit (FaaST).

Dylan S. Rankin, Jeffrey D. Krupa, Philip C. Harris, Maria Acosta Flechas, Burt Holzman, Thomas Klijnsma, Kevin Pedro, Nhan Tran, Scott Hauck, Shih-Chieh Hsu, Matthew Trahms, Kelvin Lin, Yu Lou, Ta-Wei Ho, Javier M. Duarte, Mia Liu

Proceedings of the 2020 IEEE/ACM International Workshop on Heterogeneous High-performance Reconfigurable Computing, 2020

2019

FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing.

Javier M. Duarte, Philip C. Harris, Scott Hauck, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Suffian Khan, Benjamin Kreis, Brian Lee, Mia Liu, Vladimir Loncar, Jennifer Ngadiuba, Kevin Pedro, Brandon Perez, Maurizio Pierini, Dylan S. Rankin, Nhan Tran, Matthew Trahms, Aristeidis Tsaris, Colin Versteeg, Ted W. Way, Dustin Werran, Zhenbin Wu

Comput. Softw. Big Sci., December, 2019

A study of the Effects of Information Security Advocacy.

Yan-Ye Lin, Hui-Mei Hsu, Shih-Chieh Hsu

Proceedings of the 23rd Pacific Asia Conference on Information Systems, 2019

2016

Constructing a Travel Risks' Evaluation Model for Tour Freelancers Based on the ANP Approach.

Chin-Tsai Lin, Shih-Chieh Hsu

Adv. Oper. Res., 2016

2015

Collective Regulatory Focus and Control Mechanisms: The Impact of Regulatory Fit on ISD Project Performance.

YuWen Hung, Shih-Chieh Hsu

Proceedings of the 23rd European Conference on Information Systems, 2015

1993

VLSI implementation of an M-array image filter based on shift register array.

Chen-Yi Lee, Jer-Min Tsai, Shih-Chieh Hsu

Integr., 1993