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ORCIDElham E Khoda
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2020 – today
- 2024
[i7]Zhixing Jiang, Dennis Yin, Elham E Khoda, Vladimir Loncar, Ekaterina Govorkova, Eric A. Moreno, Philip C. Harris, Scott Hauck, Shih-Chieh Hsu:
Ultra Fast Transformers on FPGAs for Particle Physics Experiments. CoRR abs/2402.01047 (2024)- [i6]Xiaohan Liu, ChiJui Chen, YanLun Huang, LingChi Yang, Elham E Khoda, Yihui Chen, Scott Hauck, Shih-Chieh Hsu, Bo-Cheng Lai:
FPGA Deployment of LFADS for Real-time Neuroscience Experiments. CoRR abs/2402.04274 (2024) - [i5]Zhixing Jiang, Dennis Yin, Yihui Chen, Elham E Khoda, Scott Hauck, Shih-Chieh Hsu, Ekaterina Govorkova, Philip C. Harris, Vladimir Loncar, Eric A. Moreno:
Low Latency Transformer Inference on FPGAs for Physics Applications with hls4ml. CoRR abs/2409.05207 (2024) - 2023
- [j1]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:
Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. Mach. Learn. Sci. Technol. 4(2): 25004 (2023) - 2022
- [i4]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 abs/2203.16255 (2022) - [i3]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:
Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. CoRR abs/2207.00559 (2022) - [i2]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 abs/2207.09060 (2022) - 2021
- [i1]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:
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021)
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