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Jennifer Ngadiuba
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2020 – today
- 2024
- [j13]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) - [c3]Tommaso Baldi, Javier Campos, Benjamin Hawks
Reliable edge machine learning hardware for scientific applications. VTS 2024: 1-5 - [i20]Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran:
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning. CoRR abs/2401.08777 (2024) - [i19]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 abs/2402.01876 (2024) - [i18]Chang Sun, Thea Klæboe Årrestad, Vladimir Loncar, Jennifer Ngadiuba, Maria Spiropulu:
Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip. CoRR abs/2405.00645 (2024) - [i17]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 abs/2406.19522 (2024) - 2023
- [i16]Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant:
Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation. CoRR abs/2311.14160 (2023) - [i15]Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant:
Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder. CoRR abs/2311.17162 (2023) - 2022
- [j12]Allison McCarn Deiana, Nhan Tran
Applications and Techniques for Fast Machine Learning in Science. Frontiers Big Data 5: 787421 (2022) - [j11]Pratik Jawahar
Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows. Frontiers Big Data 5: 803685 (2022) - [j10]Javier M. Duarte, Mia Liu, Jennifer Ngadiuba, Elena Cuoco
Editorial: Efficient AI in particle physics and astrophysics. Frontiers Artif. Intell. 5 (2022) - [j9]Adrian Alan Pol
Lightweight jet reconstruction and identification as an object detection task. Mach. Learn. Sci. Technol. 3(2): 25016 (2022) - [j8]Nicolò Ghielmetti
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. Mach. Learn. Sci. Technol. 3(4): 45011 (2022) - [j7]Ekaterina Govorkova
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): 154-161 (2022) - [j6]Ekaterina Govorkova
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): 414 (2022) - [i14]Adrian Alan Pol, Thea Aarrestad
Lightweight Jet Reconstruction and Identification as an Object Detection Task. CoRR abs/2202.04499 (2022) - [i13]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) - [i12]Nicolò Ghielmetti, Vladimir Loncar, Maurizio Pierini, Marcel Roed, Sioni Summers, Thea Aarrestad, Christoffer Petersson, Hampus Linander
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. CoRR abs/2205.07690 (2022) - 2021
- [j5]Jennifer Ngadiuba
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml. Mach. Learn. Sci. Technol. 2(1): 15001 (2021) - [j4]Thea Aarrestad
Fast convolutional neural networks on FPGAs with hls4ml. Mach. Learn. Sci. Technol. 2(4): 45015 (2021) - [j3]Claudionor José Nunes Coelho Jr., Aki Kuusela, Shan Li, Hao Zhuang, Jennifer Ngadiuba
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors. Nat. Mach. Intell. 3(8): 675-686 (2021) - [c2]Zhiqiang Que, Erwei Wang, Umar Marikar, Eric A. Moreno
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. ASAP 2021: 117-124 - [i11]Thea Aarrestad
Fast convolutional neural networks on FPGAs with hls4ml. CoRR abs/2101.05108 (2021) - [i10]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
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. CoRR abs/2103.05579 (2021) - [i9]Giuseppe Di Guglielmo, Farah Fahim, Christian Herwig, Manuel Blanco Valentin, Javier M. Duarte
A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC. CoRR abs/2105.01683 (2021) - [i8]Zhiqiang Que, Erwei Wang, Umar Marikar, Eric A. Moreno, Jennifer Ngadiuba, Hamza Javed, Bartlomiej Borzyszkowski, Thea Aarrestad, Vladimir Loncar, Sioni Summers, Maurizio Pierini, Peter Y. K. Cheung, Wayne Luk:
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. CoRR abs/2106.14089 (2021) - [i7]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) - 2020
- [j2]Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. Frontiers Big Data 3: 598927 (2020) - [i6]Sioni Summers, Giuseppe Di Guglielmo, Javier M. Duarte
Fast inference of Boosted Decision Trees in FPGAs for particle physics. CoRR abs/2002.02534 (2020) - [i5]Giuseppe Di Guglielmo, Javier M. Duarte
Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML. CoRR abs/2003.06308 (2020) - [i4]Claudionor José Nunes Coelho Jr., Aki Kuusela, Hao Zhuang, Thea Aarrestad
Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml. CoRR abs/2006.10159 (2020) - [i3]Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. CoRR abs/2008.03601 (2020) - [i2]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]Javier M. Duarte
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. Comput. Softw. Big Sci. 3(1) (2019) - [c1]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: 305 - 2018
- [i1]Javier M. Duarte
Fast inference of deep neural networks in FPGAs for particle physics. CoRR abs/1804.06913 (2018)
Coauthor Index
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