Alex Graves (computer scientist)

Alex Graves
Alex Graves
Alma mater	University of Edinburgh (BSc); Technical University of Munich (PhD);
Known for	Connectionist temporal classification; Neural Turing machine; Differentiable neural computer;
	Scientific career
Fields	Artificial Intelligence; Recurrent neural networks; Handwriting recognition; Speech recognition;
Institutions	DeepMind; University of Toronto; Dalle Molle Institute for Artificial Intelligence Research
Thesis	Supervised sequence labelling with recurrent neural networks (2008)
Doctoral advisor	Jürgen Schmidhuber
Website	www.cs.toronto.edu/~graves

Alex Graves is a computer scientist.^[1]

Education

Graves earned his Bachelor of Science degree in Theoretical Physics from the University of Edinburgh^[when?] and a PhD in artificial intelligence from the Technical University of Munich supervised by Jürgen Schmidhuber at the Dalle Molle Institute for Artificial Intelligence Research.^[2]^[3]

Career and research

After his PhD, Graves was postdoc working with Schmidhuber at the Technical University of Munich and Geoffrey Hinton^[4] at the University of Toronto.

At the Dalle Molle Institute for Artificial Intelligence Research, Graves trained long short-term memory (LSTM) neural networks by a novel method called connectionist temporal classification (CTC).^[5] This method outperformed traditional speech recognition models in certain applications.^[6] In 2009, his CTC-trained LSTM was the first recurrent neural network (RNN) to win pattern recognition contests, winning several competitions in connected handwriting recognition.^[7]^[8] Google uses CTC-trained LSTM for speech recognition on the smartphone.^[9]^[10]

Graves is also the creator of neural Turing machines^[11] and the closely related differentiable neural computer.^[12]^[13] In 2023, he wrote the paper Bayesian Flow Networks.^[14]

References

^ ^a ^b Alex Graves publications indexed by Google Scholar
^ Graves, Alex (2008). Supervised sequence labelling with recurrent neural networks (PDF) (PhD thesis). Technischen Universitat Munchen. OCLC 1184353689.
^ "Alex Graves". Canadian Institute for Advanced Research. Archived from the original on 1 May 2015.
^ "Marginally Interesting: What is going on with DeepMind and Google?". Blog.mikiobraun.de. 28 January 2014. Retrieved May 17, 2016.
^ Alex Graves, Santiago Fernandez, Faustino Gomez, and Jürgen Schmidhuber (2006). Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural nets. Proceedings of ICML’06, pp. 369–376.
^ Fernández, Santiago; Graves, Alex; Schmidhuber, Jürgen (2007). "An Application of Recurrent Neural Networks to Discriminative Keyword Spotting". Artificial Neural Networks – ICANN 2007. Lecture Notes in Computer Science. Vol. 4669. pp. 220–229. doi:10.1007/978-3-540-74695-9_23. ISBN 978-3-540-74693-5.
^ Graves, Alex; and Schmidhuber, Jürgen; Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks, in Bengio, Yoshua; Schuurmans, Dale; Lafferty, John; Williams, Chris K. I.; and Culotta, Aron (eds.), Advances in Neural Information Processing Systems 22 (NIPS'22), December 7th–10th, 2009, Vancouver, BC, Neural Information Processing Systems (NIPS) Foundation, 2009, pp. 545–552 https://dl.acm.org/doi/10.5555/2981780.2981848
^ Graves, A.; Liwicki, M.; Fernandez, S.; Bertolami, R.; Bunke, H.; Schmidhuber, J. (2009). "A Novel Connectionist System for Unconstrained Handwriting Recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence. 31 (5): 855–868. doi:10.1109/TPAMI.2008.137. PMID 19299860.
^ Google Research Blog. The neural networks behind Google Voice transcription. August 11, 2015. By Françoise Beaufays http://googleresearch.blogspot.co.at/2015/08/the-neural-networks-behind-google-voice.html
^ Google Research Blog. Google voice search: faster and more accurate. September 24, 2015. By Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk – Google Speech Team http://googleresearch.blogspot.co.uk/2015/09/google-voice-search-faster-and-more.html
^ "Google's Secretive DeepMind Startup Unveils a "Neural Turing Machine"". Retrieved May 17, 2016.
^ Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago (2016-10-12). "Hybrid computing using a neural network with dynamic external memory". Nature. 538 (7626): 471–476. Bibcode:2016Natur.538..471G. doi:10.1038/nature20101. ISSN 1476-4687. PMID 27732574. S2CID 205251479.
^ "Differentiable neural computers | DeepMind". DeepMind. Retrieved 2016-10-19.
^ Graves, Alex; Rupesh Kumar Srivastava; Atkinson, Timothy; Gomez, Faustino (2023). "Bayesian Flow Networks". arXiv:2308.07037 [cs.LG].

[gs-1] Alex Graves publications indexed by Google Scholar

[phd-2] Graves, Alex (2008). Supervised sequence labelling with recurrent neural networks (PDF) (PhD thesis). Technischen Universitat Munchen. OCLC 1184353689.

[3] "Alex Graves". Canadian Institute for Advanced Research. Archived from the original on 1 May 2015.

[MyUser_Blog.mikiobraun.de_May_17_2016c-4] "Marginally Interesting: What is going on with DeepMind and Google?". Blog.mikiobraun.de. 28 January 2014. Retrieved May 17, 2016.

[graves2006-5] Alex Graves, Santiago Fernandez, Faustino Gomez, and Jürgen Schmidhuber (2006). Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural nets. Proceedings of ICML’06, pp. 369–376.

[fernandez2007keyword-6] Fernández, Santiago; Graves, Alex; Schmidhuber, Jürgen (2007). "An Application of Recurrent Neural Networks to Discriminative Keyword Spotting". Artificial Neural Networks – ICANN 2007. Lecture Notes in Computer Science. Vol. 4669. pp. 220–229. doi:10.1007/978-3-540-74695-9_23. ISBN 978-3-540-74693-5.

[7] Graves, Alex; and Schmidhuber, Jürgen; Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks, in Bengio, Yoshua; Schuurmans, Dale; Lafferty, John; Williams, Chris K. I.; and Culotta, Aron (eds.), Advances in Neural Information Processing Systems 22 (NIPS'22), December 7th–10th, 2009, Vancouver, BC, Neural Information Processing Systems (NIPS) Foundation, 2009, pp. 545–552 https://dl.acm.org/doi/10.5555/2981780.2981848

[8] Graves, A.; Liwicki, M.; Fernandez, S.; Bertolami, R.; Bunke, H.; Schmidhuber, J. (2009). "A Novel Connectionist System for Unconstrained Handwriting Recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence. 31 (5): 855–868. doi:10.1109/TPAMI.2008.137. PMID 19299860.

[GoogleVoiceTranscription-9] Google Research Blog. The neural networks behind Google Voice transcription. August 11, 2015. By Françoise Beaufays http://googleresearch.blogspot.co.at/2015/08/the-neural-networks-behind-google-voice.html

[GoogleVoiceSearch-10] Google Research Blog. Google voice search: faster and more accurate. September 24, 2015. By Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk – Google Speech Team http://googleresearch.blogspot.co.uk/2015/09/google-voice-search-faster-and-more.html

[MyUser_Https:_May_17_2016c-11] "Google's Secretive DeepMind Startup Unveils a "Neural Turing Machine"". Retrieved May 17, 2016.

[DNCnature2016-12] Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago (2016-10-12). "Hybrid computing using a neural network with dynamic external memory". Nature. 538 (7626): 471–476. Bibcode:2016Natur.538..471G. doi:10.1038/nature20101. ISSN 1476-4687. PMID 27732574. S2CID 205251479.

[13] "Differentiable neural computers | DeepMind". DeepMind. Retrieved 2016-10-19.

[14] Graves, Alex; Rupesh Kumar Srivastava; Atkinson, Timothy; Gomez, Faustino (2023). "Bayesian Flow Networks". arXiv:2308.07037 [cs.LG].

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Alex Graves (computer scientist)

Education

Career and research

References

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