Building high-level features using large scale unsupervised learning. - Quoc V. Le; Marc'Aurelio Ranzato; Rajat Monga; Matthieu Devin; Greg Corrado; Kai Chen 010; Jeffrey Dean; Andrew Y. Ng (ICML, 2012)

Large Scale Distributed Deep Networks. - Jeffrey Dean; Greg Corrado; Rajat Monga; Kai Chen 010; Matthieu Devin; Quoc V. Le; Mark Z. Mao; Marc'Aurelio Ranzato; Andrew W. Senior; Paul A. Tucker; Ke Yang; Andrew Y. Ng (NIPS, 2012)

On rectified linear units for speech processing. - Matthew D. Zeiler; Marc'Aurelio Ranzato; Rajat Monga; Mark Z. Mao; K. Yang; Quoc Viet Le; Patrick Nguyen; Andrew W. Senior; Vincent Vanhoucke; Jeffrey Dean; Geoffrey E. Hinton (ICASSP, 2013)

Sequence discriminative distributed training of long short-term memory recurrent neural networks. - Hasim Sak; Oriol Vinyals; Georg Heigold; Andrew W. Senior; Erik McDermott; Rajat Monga; Mark Z. Mao (INTERSPEECH, 2014)

Beyond short snippets: Deep networks for video classification. - Joe Yue-Hei Ng; Matthew J. Hausknecht; Sudheendra Vijayanarasimhan; Oriol Vinyals; Rajat Monga; George Toderici (CVPR, 2015)

Deep Networks With Large Output Spaces. - Sudheendra Vijayanarasimhan; Jonathon Shlens; Rajat Monga; Jay Yagnik (ICLR (Workshop), 2015)

TensorFlow: A System for Large-Scale Machine Learning. - Martín Abadi; Paul Barham 001; Jianmin Chen; Zhifeng Chen; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Geoffrey Irving; Michael Isard; Manjunath Kudlur; Josh Levenberg; et al. (OSDI, 2016)

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. - Martín Abadi; Ashish Agarwal; Paul Barham 001; Eugene Brevdo; Zhifeng Chen; Craig Citro; Gregory S. Corrado; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Ian J. Goodfellow; et al. (CoRR, 2016)

TensorFlow: A system for large-scale machine learning. - Martín Abadi; Paul Barham 001; Jianmin Chen; Zhifeng Chen; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Geoffrey Irving; Michael Isard; Manjunath Kudlur; Josh Levenberg; et al. (CoRR, 2016)

Revisiting Distributed Synchronous SGD. - Jianmin Chen; Rajat Monga; Samy Bengio; Rafal Józefowicz (CoRR, 2016)

Dynamic control flow in large-scale machine learning. - Yuan Yu; Martín Abadi; Paul Barham 001; Eugene Brevdo; Mike Burrows; Andy Davis; Jeff Dean; Sanjay Ghemawat; Tim Harley; Peter Hawkins; Michael Isard; Manjunath Kudlur; et al. (EuroSys, 2018)

TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning. - Akshay Agrawal; Akshay Naresh Modi; Alexandre Passos; Allen Lavoie; Ashish Agarwal; Asim Shankar; Igor Ganichev; Josh Levenberg; Mingsheng Hong; Rajat Monga; Shanqing Cai (SysML, 2019)

TensorFlow.js: Machine Learning For The Web and Beyond. - Daniel Smilkov; Nikhil Thorat; Yannick Assogba; Ann Yuan; Nick Kreeger; Ping Yu; Kangyi Zhang; Shanqing Cai; Eric Nielsen; David Soergel; Stan Bileschi; Michael Terry; et al. (SysML, 2019)

SysML: The New Frontier of Machine Learning Systems. - Alexander Ratner; Dan Alistarh; Gustavo Alonso; David G. Andersen; Peter Bailis; Sarah Bird; Nicholas Carlini; Bryan Catanzaro; Eric S. Chung; Bill Dally; Jeff Dean; Inderjit S. Dhillon; et al. (CoRR, 2019)

TRACE: A Time-Relational Approximate Cubing Engine for Fast Data Insights. - Suharsh Sivakumar; Jonathan Shen; Rajat Monga (CoRR, 2024)