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Lucas Theis

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
2017 · Christian Ledig, Lucas Theis, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 12,693
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
2016 · Ledig, Christian, Theis, Lucas, et al. · arXiv (Cornell University) · 989
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A note on the evaluation of generative models
2015 · Theis, Lucas, Oord, Aäron van den, et al. · arXiv (Cornell University) · 699
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Lossy Image Compression with Compressive Autoencoders
2017 · Theis, Lucas, Shi, Wenzhe, et al. · arXiv (Cornell University) · 579
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Fast Face-Swap Using Convolutional Neural Networks
2017 · Iryna Korshunova, Wenzhe Shi, et al. · IEEE/CVF International Conference on Computer Vision (ICCV) · 501
HoloGAN: Unsupervised Learning of 3D Representations From Natural Images
2019 · Thu Nguyen-Phuoc, Chuan Li, et al. · IEEE/CVF International Conference on Computer Vision (ICCV) · 338
Amortised MAP Inference for Image Super-resolution
2016 · Sønderby, Casper Kaae, Caballero, Jose, et al. · arXiv (Cornell University) · 302
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Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
2014 · Kümmerer, Matthias, Theis, Lucas, et al. · arXiv (Cornell University) · 239
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Lossy Image Compression with Compressive Autoencoders
2020 · Huszar, Ferenc, Theis, Lucas, et al. · Apollo (University of Cambridge) · 237
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Benchmarking Spike Rate Inference in Population Calcium Imaging
2016 · Lucas Theis, Philipp Berens, et al. · Neuron · 196
HoloGAN: Unsupervised Learning of 3D Representations From Natural Images
2019 · Thu Nguyen-Phuoc, Chuan Li, et al. · IEEE International Conference on Computer Vision Workshops · 178
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data
2018 · Philipp Berens, Jeremy Freeman, et al. · PLoS Computational Biology · 175
Generative Image Modeling Using Spatial LSTMs
2015 · Theis, Lucas, Bethge, Matthias · arXiv (Cornell University) · 150
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Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize
2017 · Aitken, Andrew, Ledig, Christian, et al. · arXiv (Cornell University) · 137
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Faster gaze prediction with dense networks and Fisher pruning
2018 · Theis, Lucas, Korshunova, Iryna, et al. · arXiv (Cornell University) · 119
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Is the deconvolution layer the same as a convolutional layer?
2016 · Shi, Wenzhe, Caballero, Jose, et al. · arXiv (Cornell University) · 113
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Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents
2013 · André M. Chagas, Lucas Theis, et al. · Frontiers in Neural Circuits · 83
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An Introduction to Neural Data Compression
2023 · Yibo Yang, Stephan Mandt, et al. · Foundations and Trends® in Computer Graphics and Vision · 74
Universally Quantized Neural Compression
2020 · Agustsson, Eirikur, Theis, Lucas · arXiv (Cornell University) · 63
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Addressing delayed feedback for continuous training with neural networks in CTR prediction
2019 · Sofia Ira Ktena, Alykhan Tejani, et al. · ACM Conference on Recommender Systems (RecSys) · 57
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C3: High-Performance and Low-Complexity Neural Compression from a Single Image or Video
2024 · Hyunjik Kim, Matthias Bauer, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 55
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Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification
2013 · Lucas Theis, Andrè Maia Chagas, et al. · PLoS Computational Biology · 50
Mixtures of Conditional Gaussian Scale Mixtures Applied to Multiscale Image Representations
2012 · Lucas Theis, Reshad Hosseini, et al. · PLoS ONE · 33
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An Introduction to Neural Data Compression
2023 · Yibo Yang, Stephan Mandt, et al. · 32
A coding theorem for the rate-distortion-perception function
2021 · Theis, Lucas, Wagner, Aaron B. · arXiv (Cornell University) · 28
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Works count: 67
Citation count: 18,340
H-index: 26
I10-index: 35
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