Javier M. Duarte

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 73

Top Topics

Data Compression

High Energy Physics

Top Venues

Mach. Learn. Sci. Technol.

Frontiers Big Data

Comput. Softw. Big Sci.

Publications

Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. CoRR (2024)
Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin
Reliable edge machine learning hardware for scientific applications. CoRR (2024)
Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin
Reliable edge machine learning hardware for scientific applications. VTS (2024)
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)
Patrick Odagiu, Zhiqiang Que, Javier M. Duarte, Johannes Haller, Gregor Kasieczka, Artur Lobanov, Vladimir Loncar, Wayne Luk, Jennifer Ngadiuba, Maurizio Pierini, Philipp Rincke, Arpita Seksaria, Sioni Summers, Andre Sznajder, Alexander D. Tapper, Thea Klæboe Årrestad
Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. CoRR (2024)
Javier Campos, Zhen Dong, Javier M. Duarte, Amir Gholami, Michael W. Mahoney, Jovan Mitrevski, Nhan Tran
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs. CoRR (2023)
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 (2023)
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. FPL (2023)
Farouk Mokhtar, Joosep Pata, Javier M. Duarte, Eric Wulff, Maurizio Pierini, Jean-Roch Vlimant
Progress towards an improved particle flow algorithm at CMS with machine learning. CoRR (2023)
Luke McDermott, Jason Weitz, Dmitri Demler, Daniel Cummings, Nhan Tran, Javier M. Duarte
Neural Architecture Codesign for Fast Bragg Peak Analysis. CoRR (2023)
Raghav Kansal, Carlos Pareja, Zichun Hao, Javier M. Duarte
JetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physics. J. Open Source Softw. 8 (91) (2023)
Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez
Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC. CoRR (2023)
Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez
Differentiable Earth mover's distance for data compression at the high-luminosity LHC. Mach. Learn. Sci. Technol. 4 (4) (2023)
Rommie E. Amaro, Jiunn-Yeu Chen, Javier M. Duarte, Thomas E. Hutton, Christopher Irving, Martin C. Kandes, Amit Majumdar, Dmitry Y. Mishin, Mai H. Nguyen, Paul Rodríguez, Fernando Silva, Robert S. Sinkovits, Shawn M. Strande, Mahidhar Tatineni, Leon Si Tran, Nicole Wolter
Voyager - An Innovative Computational Resource for Artificial Intelligence & Machine Learning Applications in Science and Engineering. PEARC (2023)
Wahid Bhimji, D. Carder, Eli Dart, Javier M. Duarte, Ian Fisk, Robert W. Gardner, Chin Guok, Bo Jayatilaka, Tom Lehman, M. Lin, C. Maltzahn, Shawn McKee, Mark S. Neubauer, O. Rind, O. Shadura, N. V. Tran, P. van Gemmeren, Gordon Watts, B. A. Weaver, Frank Würthwein
Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access. Comput. Softw. Big Sci. 7 (1) (2023)
Anni Li, Venkat Krishnamohan, Raghav Kansal, Rounak Sen, Steven Tsan, Zhaoyu Zhang, Javier M. Duarte
Induced Generative Adversarial Particle Transformers. CoRR (2023)
Javier M. Duarte, Haoyang Li, Avik Roy, Ruike Zhu, E. 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. Mach. Learn. Sci. Technol. 4 (4) (2023)
Joosep Pata, Eric Wulff, Farouk Mokhtar, David Southwick, Mengke Zhang, Maria Girone, Javier M. Duarte
Scalable neural network models and terascale datasets for particle-flow reconstruction. CoRR (2023)
Breno Orzari, Nadezda Chernyavskaya, Raphael Cóbe, Javier M. Duarte, Jefferson F. Coelho, Dimitrios Gunopulos, Raghav Kansal, Maurizio Pierini, Thiago Tomei, Mary Touranakou
LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows. Mach. Learn. Sci. Technol. 4 (4) (2023)
Farouk Mokhtar, Raghav Kansal, Javier M. Duarte
Do graph neural networks learn traditional jet substructure? CoRR (2022)
Javier M. Duarte, Haoyang Li, Avik Roy, Ruike Zhu, E. 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 (2022)
Ekaterina Govorkova, Ema Puljak, Thea Aarrestad, Thomas James, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Nicolò Ghielmetti, Maksymilian Graczyk, Sioni Summers, Jennifer Ngadiuba, Thong Q. Nguyen, Javier M. Duarte, Zhenbin Wu
Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. Nat. Mach. Intell. 4 (2) (2022)
E. 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, Daniel S. Katz, Volodymyr V. Kindratenko, Christine R. Kirkpatrick, Kati Lassila-Perini, Ravi K. Madduri, Mark S. Neubauer, Fotis E. Psomopoulos, Avik Roy, Oliver Rübel, Zhizhen Zhao, Ruike Zhu
FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. CoRR (2022)
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
QONNX: Representing Arbitrary-Precision Quantized Neural Networks. CoRR (2022)
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
Physics Community Needs, Tools, and Resources for Machine Learning. CoRR (2022)
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
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. CoRR (2022)
Javier M. Duarte, Mia Liu, Jennifer Ngadiuba, Elena Cuoco, Jesse Thaler
Editorial: Efficient AI in particle physics and astrophysics. Frontiers Artif. Intell. 5 (2022)
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
Graph Neural Networks for Charged Particle Tracking on FPGAs. Frontiers Big Data 5 (2022)
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 (2022)
Joosep Pata, Javier M. Duarte, Farouk Mokhtar, Eric Wulff, Jieun Yoo, Jean-Roch Vlimant, Maurizio Pierini, Maria Girone
Machine Learning for Particle Flow Reconstruction at CMS. CoRR (2022)
Javier M. Duarte, Nhan Tran, Benjamin Hawks, Christian Herwig, Jules Muhizi, Shvetank Prakash, Vijay Janapa Reddi
FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning. CoRR (2022)
Ekaterina Govorkova, Ema Puljak, Thea Aarrestad, Thomas James, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Nicolò Ghielmetti, Maksymilian Graczyk, Sioni Summers, Jennifer Ngadiuba, Thong Q. Nguyen, Javier M. Duarte, Zhenbin Wu
Author Correction: Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. Nat. Mach. Intell. 4 (4) (2022)
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 (2022)
Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopoulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders. CoRR (2022)
Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant
Particle-based fast jet simulation at the LHC with variational autoencoders. Mach. Learn. Sci. Technol. 3 (3) (2022)
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
Applications and Techniques for Fast Machine Learning in Science. Frontiers Big Data 5 (2022)
Pratik Jawahar, Thea Aarrestad, Nadezda Chernyavskaya, Maurizio Pierini, Kinga Anna Wozniak, Jennifer Ngadiuba, Javier M. Duarte, Steven Tsan
Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows. Frontiers Big Data 5 (2022)
Raghav Kansal, Anni Li, Javier M. Duarte, Nadezda Chernyavskaya, Maurizio Pierini, Breno Orzari, Thiago Tomei
On the Evaluation of Generative Models in High Energy Physics. CoRR (2022)
Joosep Pata, Javier M. Duarte, Jean-Roch Vlimant, Maurizio Pierini, Maria Spiropulu
MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks. CoRR (2021)
Yifan Chen, E. A. Huerta, Javier M. Duarte, Philip C. Harris, Daniel S. Katz, Mark S. Neubauer, Daniel Diaz, Farouk Mokhtar, Raghav Kansal, Sang Eon Park, Volodymyr V. Kindratenko, Zhizhen Zhao, Roger Rusack
A FAIR and AI-ready Higgs Boson Decay Dataset. CoRR (2021)
Farouk Mokhtar, Raghav Kansal, Daniel Diaz, Javier M. Duarte, Joosep Pata, Maurizio Pierini, Jean-Roch Vlimant
Explaining machine-learned particle-flow reconstruction. CoRR (2021)
Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos
Particle Cloud Generation with Message Passing Generative Adversarial Networks. NeurIPS (2021)
Colby R. Banbury, Vijay Janapa Reddi, Peter Torelli, Nat Jeffries, Csaba Király, Jeremy Holleman, Pietro Montino, David Kanter, Pete Warden, Danilo Pau, Urmish Thakker, Antonio Torrini, Jay Cordaro, Giuseppe Di Guglielmo, Javier M. Duarte, Honson Tran, Nhan Tran, Wenxu Niu, Xuesong Xu
MLPerf Tiny Benchmark. NeurIPS Datasets and Benchmarks (2021)
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
GPU coprocessors as a service for deep learning inference in high energy physics. Mach. Learn. Sci. Technol. 2 (3) (2021)
Giuseppe Di Guglielmo, Farah Fahim, Christian Herwig, Manuel Blanco Valentin, Javier M. Duarte, Cristian Gingu, Philip C. Harris, James Hirschauer, Martin Kwok, Vladimir Loncar, Yingyi Luo, Llovizna Miranda, Jennifer Ngadiuba, Daniel Noonan, Seda Ogrenci Memik, Maurizio Pierini, Sioni Summers, Nhan Tran
A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC. CoRR (2021)
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, 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
Applications and Techniques for Fast Machine Learning in Science. CoRR (2021)
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
Fast convolutional neural networks on FPGAs with hls4ml. Mach. Learn. Sci. Technol. 2 (4) (2021)
Colby R. Banbury, Vijay Janapa Reddi, Peter Torelli, Jeremy Holleman, Nat Jeffries, Csaba Király, Pietro Montino, David Kanter, Sebastian Ahmed, Danilo Pau, Urmish Thakker, Antonio Torrini, Pete Warden, Jay Cordaro, Giuseppe Di Guglielmo, Javier M. Duarte, Stephen Gibellini, Videet Parekh, Honson Tran, Nhan Tran, Wenxu Niu, Xuesong Xu
MLPerf Tiny Benchmark. CoRR (2021)
Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference. CoRR (2021)
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
Fast convolutional neural networks on FPGAs with hls4ml. CoRR (2021)
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 Neubauer, Isobel Ojalvo, Savannah Thais
Graph Neural Networks for Charged Particle Tracking on FPGAs. CoRR (2021)
Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz, Javier M. Duarte, Sukanya Krishna, Farouk Mokhtar, Jean-Roch Vlimant, Maurizio Pierini
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. CoRR (2021)
Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant, Javier M. Duarte, Joshua Job, Daniel A. Lidar, Maria Spiropulu
Charged particle tracking with quantum annealing optimization. Quantum Mach. Intell. 3 (2) (2021)
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
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml. Mach. Learn. Sci. Technol. 2 (1) (2021)
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 Orgrenci-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
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. CoRR (2021)
Gage DeZoort, Savannah Thais, Isobel Ojalvo, Peter Elmer, Vesal Razavimaleki, Javier M. Duarte, Markus Atkinson, Mark Neubauer
Charged particle tracking via edge-classifying interaction networks. CoRR (2021)
Gage DeZoort, Savannah Thais, Javier M. Duarte, Vesal Razavimaleki, Markus Atkinson, Isobel Ojalvo, Mark S. Neubauer, Peter Elmer
Charged Particle Tracking via Edge-Classifying Interaction Networks. Comput. Softw. Big Sci. 5 (1) (2021)
Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference. Frontiers Artif. Intell. 4 (2021)
Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos
Particle Cloud Generation with Message Passing Generative Adversarial Networks. CoRR (2021)
Sioni Summers, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Duc Hoang, Sergo Jindariani, Edward Kreinar, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Nhan Tran, Zhenbin Wu
Fast inference of Boosted Decision Trees in FPGAs for particle physics. CoRR (2020)
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
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. CoRR (2020)
Raghav Kansal, Javier M. Duarte, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. CoRR (2020)
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
Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML. CoRR (2020)
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
FPGAs-as-a-Service Toolkit (FaaST). H2RC@SC (2020)
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
GPU coprocessors as a service for deep learning inference in high energy physics. CoRR (2020)
Aneesh Heintz, Vesal Razavimaleki, Javier M. Duarte, Gage DeZoort, Isobel Ojalvo, Savannah Thais, Markus Atkinson, Mark 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
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs. CoRR (2020)
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
FPGAs-as-a-Service Toolkit (FaaST). CoRR (2020)
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
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. Frontiers Big Data 3 (2020)
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
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. Comput. Softw. Big Sci. 3 (1) (2019)
Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Ryan A. Rivera, Sioni Summers, Nhan Tran, Zhenbin Wu
Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. FPGA (2019)
Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant, Javier M. Duarte, Joshua Job, Daniel A. Lidar, Maria Spiropulu
Charged particle tracking with quantum annealing-inspired optimization. CoRR (2019)
Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Jennifer Ngadiuba, Maurizio Pierini, Ryan A. Rivera, Nhan Tran, Zhenbin Wu
Fast inference of deep neural networks in FPGAs for particle physics. CoRR (2018)
Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier M. Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Alexander Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemyslaw Karpinski, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark Neubauer, Harvey B. Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel N. Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Andrew Stewart, Bob Stienen, Ian Stockdale, Giles Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata
Machine Learning in High Energy Physics Community White Paper. CoRR (2018)