Alert button
Picture for Mia Liu

Mia Liu

Alert button

Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics

Feb 19, 2024
Siqi Miao, Zhiyuan Lu, Mia Liu, Javier Duarte, Pan Li

Viaarxiv icon

Interpretable Geometric Deep Learning via Learnable Randomness Injection

Oct 30, 2022
Siqi Miao, Yunan Luo, Mia Liu, Pan Li

Figure 1 for Interpretable Geometric Deep Learning via Learnable Randomness Injection
Figure 2 for Interpretable Geometric Deep Learning via Learnable Randomness Injection
Figure 3 for Interpretable Geometric Deep Learning via Learnable Randomness Injection
Figure 4 for Interpretable Geometric Deep Learning via Learnable Randomness Injection
Viaarxiv icon

Data Science and Machine Learning in Education

Jul 19, 2022
Gabriele Benelli, Thomas Y. Chen, Javier Duarte, Matthew Feickert, Matthew Graham, Lindsey Gray, Dan Hackett, Phil 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

Figure 1 for Data Science and Machine Learning in Education
Viaarxiv icon

Physics Community Needs, Tools, and Resources for Machine Learning

Mar 30, 2022
Philip Harris, Erik Katsavounidis, William Patrick McCormack, Dylan 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 Neubauer, Javier Duarte, Georgia Karagiorgi, Mia Liu

Figure 1 for Physics Community Needs, Tools, and Resources for Machine Learning
Figure 2 for Physics Community Needs, Tools, and Resources for Machine Learning
Figure 3 for Physics Community Needs, Tools, and Resources for Machine Learning
Figure 4 for Physics Community Needs, Tools, and Resources for Machine Learning
Viaarxiv icon

Applications and Techniques for Fast Machine Learning in Science

Oct 25, 2021
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bahr, Jurgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomas E. Muller 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 Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

Figure 1 for Applications and Techniques for Fast Machine Learning in Science
Figure 2 for Applications and Techniques for Fast Machine Learning in Science
Figure 3 for Applications and Techniques for Fast Machine Learning in Science
Figure 4 for Applications and Techniques for Fast Machine Learning in Science
Viaarxiv icon

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

Mar 23, 2021
Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P. Carloni, Giuseppe Di Guglielmo, Philip Harris, Jeffrey Krupa, Dylan Rankin, Manuel Blanco Valentin, Josiah Hester, Yingyi Luo, John Mamish, Seda Orgrenci-Memik, Thea Aarrestad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, Zhenbin Wu

Figure 1 for hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices
Figure 2 for hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices
Figure 3 for hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices
Figure 4 for hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices
Viaarxiv icon

Fast convolutional neural networks on FPGAs with hls4ml

Jan 13, 2021
Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Dylan Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang

Figure 1 for Fast convolutional neural networks on FPGAs with hls4ml
Figure 2 for Fast convolutional neural networks on FPGAs with hls4ml
Figure 3 for Fast convolutional neural networks on FPGAs with hls4ml
Figure 4 for Fast convolutional neural networks on FPGAs with hls4ml
Viaarxiv icon

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs

Nov 30, 2020
Aneesh Heintz, Vesal Razavimaleki, Javier Duarte, Gage DeZoort, Isobel Ojalvo, Savannah Thais, Markus Atkinson, Mark Neubauer, Lindsey Gray, Sergo Jindariani, Nhan Tran, Philip Harris, Dylan Rankin, Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Mia Liu, Edward Kreinar, Zhenbin Wu

Figure 1 for Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
Figure 2 for Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
Figure 3 for Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
Figure 4 for Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
Viaarxiv icon