Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Eric Moreno

Eric Moreno

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
* 66 pages, 13 figures, 5 tables 
  Access Paper or Ask Questions

Accelerating Recurrent Neural Networks for Gravitational Wave Experiments


Jun 26, 2021
Zhiqiang Que, Erwei Wang, Umar Marikar, Eric Moreno, Jennifer Ngadiuba, Hamza Javed, Bartłomiej Borzyszkowski, Thea Aarrestad, Vladimir Loncar, Sioni Summers, Maurizio Pierini, Peter Y Cheung, Wayne Luk

Figure 1 for Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
Figure 2 for Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
Figure 3 for Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
Figure 4 for Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
* Accepted at the 2021 32nd IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP) 
  Access Paper or Ask Questions