| An image is worth 16x16 words: Transformers for image recognition at scale A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ... arXiv preprint arXiv:2010.11929, 2020 | 56233 | 2020 |
| Vivit: A video vision transformer A Arnab, M Dehghani, G Heigold, C Sun, M Lučić, C Schmid Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 2722 | 2021 |
| Object-centric learning with slot attention F Locatello, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ... Advances in neural information processing systems 33, 11525-11538, 2020 | 907 | 2020 |
| End-to-end text-dependent speaker verification G Heigold, I Moreno, S Bengio, N Shazeer 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 805 | 2016 |
| Small-footprint keyword spotting using deep neural networks G Chen, C Parada, G Heigold 2014 IEEE international conference on acoustics, speech and signal …, 2014 | 715 | 2014 |
| Multilingual acoustic models using distributed deep neural networks G Heigold, V Vanhoucke, A Senior, P Nguyen, MA Ranzato, M Devin, ... 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 397 | 2013 |
| An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint (2020) A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ... arXiv preprint arXiv:2010.11929, 2010 | 349 | 2010 |
| An empirical study of learning rates in deep neural networks for speech recognition A Senior, G Heigold, MA Ranzato, K Yang 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 234 | 2013 |
| Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... arXiv preprint arXiv:2111.12594, 2021 | 225 | 2021 |
| Word embeddings for speech recognition. S Bengio, G Heigold Interspeech, 1053-1057, 2014 | 191 | 2014 |
| Asynchronous optimization for sequence training of neural networks G Heigold, E McDermott, VO Vanhoucke, AW Senior, MAU Bacchiani US Patent 10,019,985, 2018 | 176 | 2018 |
| Sequence discriminative distributed training of long short-term memory recurrent neural networks H Sak, O Vinyals, G Heigold, A Senior, E McDermott, R Monga, M Mao entropy 15 (16), 17-18, 2014 | 173 | 2014 |
| The RWTH aachen university open source speech recognition system. D Rybach, C Gollan, G Heigold, B Hoffmeister, J Lööf, R Schlüter, H Ney Interspeech, 2111-2114, 2009 | 148 | 2009 |
| Speech recognition process G Heigold, PAP Nguyen, M Weintraub, VO Vanhoucke US Patent 8,775,177, 2014 | 142 | 2014 |
| A linguistic evaluation of rule-based, phrase-based, and neural MT engines A Burchardt, V Macketanz, J Dehdari, G Heigold, P Jan-Thorsten, ... The Prague bulletin of mathematical linguistics 108 (1), 159, 2017 | 113 | 2017 |
| How robust are character-based word embeddings in tagging and MT against wrod scramlbing or randdm nouse? G Heigold, G Neumann, J van Genabith arXiv preprint arXiv:1704.04441, 2017 | 84 | 2017 |
| Cross-lingual, character-level neural morphological tagging R Cotterell, G Heigold arXiv preprint arXiv:1708.09157, 2017 | 81 | 2017 |
| Neural networks for speaker verification G Heigold, S Bengio, IL Moreno US Patent 9,978,374, 2018 | 80 | 2018 |
| A Gaussian mixture model layer jointly optimized with discriminative features within a deep neural network architecture E Variani, E McDermott, G Heigold 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 79 | 2015 |
| The RWTH 2007 TC-STAR evaluation system for european English and Spanish. J Lööf, C Gollan, S Hahn, G Heigold, B Hoffmeister, C Plahl, D Rybach, ... Interspeech, 2145-2148, 2007 | 79 | 2007 |
