theis.io

Lucas Theis

I am a machine learning researcher at Twitter. Working on image enhancement and compression. I joined Twitter through the acquisition of Magic Pony Technology. A London based startup. Before that, I did my PhD at the Max Planck Research School for Neural Information Processing. In Tübingen, working in the lab of Matthias Bethge. Topics I am interested in include Bayesian inference, deep learning, natural image statistics, and computational neuroscience. Amortised MAP Inference for Image Super-resolution.

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Lucas Theis | theis.io Reviews

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I am a machine learning researcher at Twitter. Working on image enhancement and compression. I joined Twitter through the acquisition of Magic Pony Technology. A London based startup. Before that, I did my PhD at the Max Planck Research School for Neural Information Processing. In Tübingen, working in the lab of Matthias Bethge. Topics I am interested in include Bayesian inference, deep learning, natural image statistics, and computational neuroscience. Amortised MAP Inference for Image Super-resolution.

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1 lucas theis

2 curriculum vitae

3 lucas@theis io

4 lucastheis

5 on the web

6 crossvalidated

7 github

8 twitter

9 facebook

10 flickr

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Lucas Theis | theis.io Reviews

https://theis.io

I am a machine learning researcher at Twitter. Working on image enhancement and compression. I joined Twitter through the acquisition of Magic Pony Technology. A London based startup. Before that, I did my PhD at the Max Planck Research School for Neural Information Processing. In Tübingen, working in the lab of Matthias Bethge. Topics I am interested in include Bayesian inference, deep learning, natural image statistics, and computational neuroscience. Amortised MAP Inference for Image Super-resolution.

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theis.io

1

Lucas Theis

http://theis.io/publications/19

Amortised MAP Inference for Image Super-resolution. ArXiv:1610.04490 , 2016. Unpublished{Sønderby2016a, author = "C. Sønderby and J. Caballero and L. Theis and W. Shi and F. Huszár", title = "Amortised MAP Inference for Image Super-resolution", year = 2016, month = "Oct", keywords = "super-resolution, deep learning", url = "https:/ arxiv.org/abs/1610.04490", note = "arXiv:1610.04490 " }.

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Lucas Theis

http://theis.io/publications/a.+tejani

Unpublished Papers by A. Tejani. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. ArXiv:1609.04802, 2016.

3

Lucas Theis

http://theis.io/publications/tag/deep+learning

Publications with the keyword deep learning. Lossy Image Compression with Compressive Autoencoders. International Conference on Learning Representations, 2017. Amortised MAP Inference for Image Super-resolution. ArXiv:1610.04490 , 2016. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. ArXiv:1609.04802, 2016. Generative Image Modeling Using Spatial LSTMs. Advances in Neural Information Processing Systems 28, 2015. ICLR Workshop, 2015.

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Lucas Theis

http://theis.io/publications/a.+aitken

Unpublished Papers by A. Aitken. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. ArXiv:1609.04802, 2016.

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Lucas Theis

http://theis.io/publications/20

Lossy Image Compression with Compressive Autoencoders. International Conference on Learning Representations, 2017. Inproceedings{Theis2017a, author = "L. Theis and W. Shi and A. Cunningham and F. Huszár", title = "Lossy Image Compression with Compressive Autoencoders", year = 2017, booktitle = "International Conference on Learning Representations", keywords = "compression, deep learning", url = "https:/ openreview.net/pdf?

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BETHGE LAB · People

http://bethgelab.org/people

49 7071 29 89017. My research goal is to understand how the brain makes sense of its high-dimensional sensory input. In particular, I seek to understand the formation of distributed neural representations in the visual system by studying deep neural networks, natural image statistics, unsupervised learning, and neural population coding, and by developing new data-analysis tools. 49 7071 29 89018. Judith Lam (parental leave). 49 7071 29 89019. 49 7071 29 88833. 49 7071 29 88906. 49 7071 29 88908. I am a M...

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Lucas Theis

I am a machine learning researcher at Twitter. Working on image enhancement and compression. I joined Twitter through the acquisition of Magic Pony Technology. A London based startup. Before that, I did my PhD at the Max Planck Research School for Neural Information Processing. In Tübingen, working in the lab of Matthias Bethge. Topics I am interested in include Bayesian inference, deep learning, natural image statistics, and computational neuroscience. Amortised MAP Inference for Image Super-resolution.

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