Mia Liu

29 papers A* 3Journal 25Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
PQuantML: A Tool for End-to-End Hardware-aware Model Compression.
CoRR
Roope Niemi, Anastasiia Petrovych, Arghya Ranjan Das, Enrico Lupi, Chang Sun, Dimitrios Danopoulos, Marlon Joshua Helbing, Mia Liu, Sebastian Dittmeier, Michael Kagan, Vladimir Loncar, Maurizio Pierini
2025 J jnl
Building Machine Learning Challenges for Anomaly Detection in Science.
CoRR
Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova, Wahid Bhimji, Wei-Lun Chao, Chris Harris, Shih-Chieh Hsu, Hilmar Lapp, Mark S. Neubauer, Josephine M. Namayanja, Aneesh Subramanian, Philip C. Harris, Advaith Anand, David Edward Carlyn, Subhankar Ghosh, Christopher G. Lawrence, Eric A. Moreno, Ryan Raikman, Jiaman Wu, Ziheng Zhang, Bayu Adhi, Mohammad Ahmadi Gharehtoragh, Saúl Alonso-Monsalve, Marta Babicz, Furqan Baig, Namrata Banerji, William Bardon, Tyler Barna, Tanya Y. Berger-Wolf, Adji Bousso Dieng, Micah Brachman, Quentin Buat, David C. Y. Hui, Phuong Cao, Franco Cerino, Yi-Chun Chang, Shivaji Chaulagain, An-Kai Chen, Deming Chen, Eric Chen, Chia-Jui Chou, Zih-Chen Ciou, Miles Cochran-Branson, Artur Cordeiro Oudot Choi, Michael Coughlin, Matteo Cremonesi, Maria Dadarlat, Peter Darch, Malina Desai, Daniel Diaz, Steven Dillmann, Javier M. Duarte, Isla Duporge, Urbas Ekka, Saba Entezari Heravi, Hao Fang, Rian Flynn, Geoffrey Fox, Emily Freed, Hang Gao, Jing Gao, Julia Gonski, Matthew J. Graham, Abolfazl Hashemi, Scott Hauck, James Hazelden, Joshua Henry Peterson, Duc Hoang, Wei Hu, Mirco Hünnefeld, David Hyde, Vandana P. Janeja, Nattapon Jaroenchai, Haoyi Jia, Yunfan Kang, Maksim Kholiavchenko, Elham E Khoda, Sangin Kim, Aditya Kumar, Bo-Cheng Lai, Trung Le, Chi-Wei Lee, Janghyeon Lee, Shaocheng Lee, Suzan van der Lee, Charles Lewis, Haitong Li, Haoyang Li, Henry Liao, Mia Liu, Xiaolin Liu, Xiulong Liu, Vladimir Loncar, Fangzheng Lyu, Ilya Makarov, Abhishikth Mallampalli Chen-Yu Mao, Alexander Michels, Alexander Migala, Farouk Mokhtar, Mathieu Morlighem
2025 J jnl
Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction.
CoRR
Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou, Siqi Miao, Amit Saha, Advaith Anand, Kilian Lieret, Gage DeZoort, Mia Liu, Javier M. Duarte, Pan Li, Shih-Chieh Hsu
2025 J jnl
SuperSONIC: Cloud-Native Infrastructure for ML Inferencing.
CoRR
Dmitry Kondratyev, Benedikt Riedel, Yuan-Tang Chou, Miles Cochran-Branson, Noah Paladino, David Schultz, Mia Liu, Javier M. Duarte, Philip Harris, Shih-Chieh Hsu
2025 J jnl
hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware.
CoRR
Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun, Jovan Mitrevski, Nicolò Ghielmetti, Enrico Lupi, Dimitrios Danopoulos, Vladimir Loncar, Javier M. Duarte, David Burnette, Lauri Laatu, Stylianos Tzelepis, Konstantinos Axiotis, Quentin Berthet, Haoyan Wang, Paul White, Suleyman Demirsoy, Marco Colombo, Thea Aarrestad, Sioni Summers, Maurizio Pierini, Giuseppe Di Guglielmo, Jennifer Ngadiuba, Javier Campos, Benjamin Hawks, Abhijith Gandrakota, Farah Fahim, Nhan Tran, George A. Constantinides, Zhiqiang Que, Wayne Luk, Alexander D. Tapper, Duc Hoang, Noah Paladino, Philip C. Harris, Bo-Cheng Lai, Manuel Blanco Valentin, Ryan F. Forelli, Seda Ogrenci, Lino Gerlach, Rian Flynn, Mia Liu, Daniel Diaz, Elham E Khoda, Melissa Quinnan, Russell Solares, Santosh Parajuli, Mark S. Neubauer, Christian Herwig, Ho Fung Tsoi, Dylan S. Rankin, Shih-Chieh Hsu, Scott Hauck
2024 J jnl
Corrigendum: Applications and techniques for fast machine learning in science.
Frontiers Big Data
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
2024 A* conf
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics.
ICML
Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li
2024 J jnl
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics.
CoRR
Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li
2023 A* conf
Interpretable Geometric Deep Learning via Learnable Randomness Injection.
ICLR
Siqi Miao, Yunan Luo, Mia Liu, Pan Li
2022 J jnl
Applications and Techniques for Fast Machine Learning in Science.
Frontiers Big Data
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
2022 J jnl
Data Science and Machine Learning in Education.
CoRR
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
2022 J jnl
Editorial: Efficient AI in particle physics and astrophysics.
Frontiers Artif. Intell.
Javier M. Duarte, Mia Liu, Jennifer Ngadiuba, Elena Cuoco, Jesse Thaler
2022 J jnl
Interpretable Geometric Deep Learning via Learnable Randomness Injection.
CoRR
Siqi Miao, Yunan Luo, Mia Liu, Pan Li
2022 A* conf
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism.
ICML
Siqi Miao, Mia Liu, Pan Li
2022 J jnl
Physics Community Needs, Tools, and Resources for Machine Learning.
CoRR
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
2021 J jnl
Applications and Techniques for Fast Machine Learning in Science.
CoRR
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
2021 J jnl
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml.
Mach. Learn. Sci. Technol.
Jennifer Ngadiuba, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Mia Liu, Kevin Pedro, Nhan Tran, Edward Kreinar, Sheila Sagear, Zhenbin Wu, Duc Hoang
2021 J jnl
Fast convolutional neural networks on FPGAs with hls4ml.
CoRR
Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang
2021 J jnl
Fast convolutional neural networks on FPGAs with hls4ml.
Mach. Learn. Sci. Technol.
Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang
2021 J jnl
GPU coprocessors as a service for deep learning inference in high energy physics.
Mach. Learn. Sci. Technol.
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
2021 J jnl
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices.
CoRR
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
2020 J jnl
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs.
CoRR
Aneesh Heintz, Vesal Razavimaleki, Javier M. Duarte, Gage DeZoort, Isobel Ojalvo, Savannah Thais, Markus Atkinson, Mark S. Neubauer, Lindsey Gray, Sergo Jindariani, Nhan Tran, Philip C. Harris, Dylan S. Rankin, Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Mia Liu, Edward Kreinar, Zhenbin Wu
2020 J jnl
Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML.
CoRR
Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Duc Hoang, Sergo Jindariani, Edward Kreinar, Mia Liu, Vladimir Loncar, Jennifer Ngadiuba, Kevin Pedro, Maurizio Pierini, Dylan S. Rankin, Sheila Sagear, Sioni Summers, Nhan Tran, Zhenbin Wu
2020 J jnl
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics.
CoRR
Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler, Vladimir Loncar, Maurizio Pierini, Shah Rukh Qasim, Marcel Rieger, Sioni Summers, Gerrit Van Onsem, Kinga Anna Wozniak, Jennifer Ngadiuba, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Mia Liu, Kevin Pedro, Nhan Tran, Edward Kreinar, Zhenbin Wu
2020 J jnl
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics.
Frontiers Big Data
Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler, Vladimir Loncar, Maurizio Pierini, Shah Rukh Qasim, Marcel Rieger, Sioni Summers, Gerrit Van Onsem, Kinga Anna Wozniak, Jennifer Ngadiuba, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Mia Liu, Kevin Pedro, Nhan Tran, Edward Kreinar, Zhenbin Wu
2020 — conf
FPGAs-as-a-Service Toolkit (FaaST).
H2RC@SC
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
2020 J jnl
FPGAs-as-a-Service Toolkit (FaaST).
CoRR
Dylan Sheldon 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
2020 J jnl
GPU coprocessors as a service for deep learning inference in high energy physics.
CoRR
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
2019 J jnl
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing.
Comput. Softw. Big Sci.
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