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Dan Gnanapragasam
Dan Gnanapragasam
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Title
Cited by
Cited by
Year
EnerJ: Approximate data types for safe and general low-power computation
A Sampson, W Dietl, E Fortuna, D Gnanapragasam, L Ceze, D Grossman
ACM SIGPLAN Notices 46 (6), 164-174, 2011
10002011
Kubric: A scalable dataset generator
K Greff, F Belletti, L Beyer, C Doersch, Y Du, D Duckworth, DJ Fleet, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
1992022
Pronunciation Learning with RNN-Transducers.
A Bruguier, D Gnanapragasam, L Johnson, K Rao, F Beaufays
INTERSPEECH, 2556-2560, 2017
182017
EnerJ: Approximate Data Types for Safe and General Low-Power Computation—Full Proofs
A Sampson, W Dietl, E Fortuna, D Gnanapragasam, L Ceze, D Grossman
University of Washington, Tech. Rep. UW-CSE-10-12-01, 2011
52011
A more general method for pronunciation learning
A Bruguier, D Gnanapragasam, F Beaufays, K Rao, L Johnson
Interspeech, 2017
12017
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Articles 1–5