Tim Dettmers
Tim Dettmers
University of Washington & Facebook AI Research
Verified email at cs.washington.edu - Homepage
Title
Cited by
Cited by
Year
Convolutional 2d knowledge graph embeddings
T Dettmers, P Minervini, P Stenetorp, S Riedel
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
6062018
8-bit approximations for parallelism in deep learning
T Dettmers
arXiv preprint arXiv:1511.04561, 2015
852015
Sparse networks from scratch: Faster training without losing performance
T Dettmers, L Zettlemoyer
arXiv preprint arXiv:1907.04840, 2019
632019
Deep learning in a nutshell: Core concepts
T Dettmers
NVIDIA Devblogs, 2015
272015
Understanding convolution in deep learning
T Dettmers
Retrieved March 25, 2018, 2015
182015
Which gpu (s) to get for deep learning: My experience and advice for using gpus in deep learning
T Dettmers
82014
Jack the reader-A machine reading framework
D Weissenborn, P Minervini, T Dettmers, I Augenstein, J Welbl, ...
arXiv preprint arXiv:1806.08727, 2018
62018
Deep learning in a nutshell: History and training
T Dettmers
62017
High Performance Natural Language Processing
G Ilharco, C Ilharco, I Turc, T Dettmers, F Ferreira, K Lee
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
2020
Computational and Parallel Deep Learning Perform-ance Benchmarks for the Xeon Phi
T Dettmers, H Soleimani
2016
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Articles 1–10