ELAROSCA.NET

Mihaela Rosca

I am a Research Engineer working at DeepMind. Previously I was working at Google in Zurich on NLP using neural networks. I finsihed my 4 year Computing MEng degree from Imperial College London in 2014, with first honours and a prize of excellence for an outstanding overall performance. Generative models, reinforcement learning, natural language processing, scalable and safe machine learning. Variational Approaches for Auto-Encoding GANs. Sequence-to-sequence neural network models for transliteration.

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Mihaela Rosca | elarosca.net Reviews

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I am a Research Engineer working at DeepMind. Previously I was working at Google in Zurich on NLP using neural networks. I finsihed my 4 year Computing MEng degree from Imperial College London in 2014, with first honours and a prize of excellence for an outstanding overall performance. Generative models, reinforcement learning, natural language processing, scalable and safe machine learning. Variational Approaches for Auto-Encoding GANs. Sequence-to-sequence neural network models for transliteration.

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1 github

2 google scholar

3 twitter

4 mihaela rosca

5 about me

6 education

7 professional interests

8 papers and thesis

9 talks

10 open source projects

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Mihaela Rosca | elarosca.net Reviews

https://elarosca.net

I am a Research Engineer working at DeepMind. Previously I was working at Google in Zurich on NLP using neural networks. I finsihed my 4 year Computing MEng degree from Imperial College London in 2014, with first honours and a prize of excellence for an outstanding overall performance. Generative models, reinforcement learning, natural language processing, scalable and safe machine learning. Variational Approaches for Auto-Encoding GANs. Sequence-to-sequence neural network models for transliteration.

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Mihaela Rosca

I am a Research Engineer working at DeepMind. Previously I was working at Google in Zurich on NLP using neural networks. I finsihed my 4 year Computing MEng degree from Imperial College London in 2014, with first honours and a prize of excellence for an outstanding overall performance. Generative models, reinforcement learning, natural language processing, scalable and safe machine learning. Variational Approaches for Auto-Encoding GANs. Sequence-to-sequence neural network models for transliteration.

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