Mixed precision training P Micikevicius, S Narang, J Alben, G Diamos, E Elsen, D Garcia, ... arXiv preprint arXiv:1710.03740, 2017 | 460 | 2017 |
An introduction to computational networks and the computational network toolkit D Yu, A Eversole, M Seltzer, K Yao, Z Huang, B Guenter, O Kuchaiev, ... Microsoft Technical Report MSR-TR-2014–112, 2014 | 424 | 2014 |
An introduction to computational networks and the computational network toolkit A Agarwal, E Akchurin, C Basoglu, G Chen, S Cyphers, J Droppo, ... Tech. Rep. MSR-TR-2014-112, 2014 | 424* | 2014 |
Topological network alignment uncovers biological function and phylogeny O Kuchaiev, T Milenković, V Memišević, W Hayes, N Pržulj Journal of the Royal Society Interface 7 (50), 1341-1354, 2010 | 374 | 2010 |
Integrative network alignment reveals large regions of global network similarity in yeast and human O Kuchaiev, N Pržulj Bioinformatics 27 (10), 1390-1396, 2011 | 291 | 2011 |
Geometric de-noising of protein-protein interaction networks O Kuchaiev, M Rašajski, DJ Higham, N Pržulj PLoS computational biology 5 (8), e1000454, 2009 | 161 | 2009 |
GraphCrunch 2: Software tool for network modeling, alignment and clustering O Kuchaiev, A Stevanović, W Hayes, N Pržulj BMC bioinformatics 12 (1), 1-13, 2011 | 83 | 2011 |
Factorization tricks for LSTM networks O Kuchaiev, B Ginsburg arXiv preprint arXiv:1703.10722, 2017 | 80 | 2017 |
Jasper: An end-to-end convolutional neural acoustic model J Li, V Lavrukhin, B Ginsburg, R Leary, O Kuchaiev, JM Cohen, H Nguyen, ... arXiv preprint arXiv:1904.03288, 2019 | 78 | 2019 |
Geometric evolutionary dynamics of protein interaction networks N Pržulj, O Kuchaiev, A Stevanović, W Hayes Biocomputing 2010, 178-189, 2010 | 60 | 2010 |
Training deep autoencoders for collaborative filtering O Kuchaiev, B Ginsburg arXiv preprint arXiv:1708.01715, 2017 | 48 | 2017 |
Quartznet: Deep automatic speech recognition with 1d time-channel separable convolutions S Kriman, S Beliaev, B Ginsburg, J Huang, O Kuchaiev, V Lavrukhin, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 40 | 2020 |
Stochastic gradient methods with layer-wise adaptive moments for training of deep networks B Ginsburg, P Castonguay, O Hrinchuk, O Kuchaiev, V Lavrukhin, R Leary, ... arXiv preprint arXiv:1905.11286, 2019 | 25 | 2019 |
Learning the structure of protein-protein interaction networks O Kuchaiev, N PRŽULJ Biocomputing 2009, 39-50, 2009 | 25 | 2009 |
Openseq2seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models O Kuchaiev, B Ginsburg, I Gitman, V Lavrukhin, C Case, P Micikevicius Proceedings of Workshop for NLP Open Source Software (NLP-OSS), 41-46, 2018 | 23 | 2018 |
Mixed-precision training for nlp and speech recognition with openseq2seq O Kuchaiev, B Ginsburg, I Gitman, V Lavrukhin, J Li, H Nguyen, C Case, ... arXiv preprint arXiv:1805.10387, 2018 | 21 | 2018 |
Structure of brain functional networks O Kuchaiev, PT Wang, Z Nenadic, N Przulj 2009 Annual International Conference of the IEEE Engineering in Medicine and …, 2009 | 19 | 2009 |
Nemo: a toolkit for building ai applications using neural modules O Kuchaiev, J Li, H Nguyen, O Hrinchuk, R Leary, B Ginsburg, S Kriman, ... arXiv preprint arXiv:1909.09577, 2019 | 16 | 2019 |
Topological network alignment uncovers biological function and phylogeny O Kuchaiev, T Milenkovic, V Memisevic, W Hayes, N Przulj Nature Precedings, 1-1, 2009 | 8 | 2009 |
Stochastic gradient descent algorithm in the computational network toolkit B Guenter, D Yu, A Eversole, O Kuchaiev, ML Seltzer OPT2013: NIPS 2013 Workshop on Optimization for Machine Learning, 2013 | 5 | 2013 |