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Ferenc Huszár
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Year
Photo-realistic single image super-resolution using a generative adversarial network
C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2017
125432017
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
W Shi, J Caballero, F Huszár, J Totz, AP Aitken, R Bishop, D Rueckert, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2016
69342016
Lossy image compression with compressive autoencoders
L Theis, W Shi, A Cunningham, F Huszár
International conference on learning representations, 2022
12042022
Bayesian active learning for classification and preference learning
N Houlsby, F Huszár, Z Ghahramani, M Lengyel
arXiv preprint arXiv:1112.5745, 2011
8262011
Photo-realistic single image super-resolution using a generative adversarial network [C]
C Ledig, L Theis, F Huszar, J Caballero, A Cunningham, A Acosta
Proceedings of the IEEE conference on computer vision and pattern …, 2017
7152017
Amortised MAP Inference for Image Super-resolution
C Kaae Sřnderby, J Caballero, L Theis, W Shi, F Huszár
ArXiv e-prints, arXiv: 1610.04490, 2016
517*2016
How (not) to train your generative model: Scheduled sampling, likelihood, adversary?
F Huszár
arXiv preprint arXiv:1511.05101, 2015
3362015
Algorithmic amplification of politics on Twitter
F Huszár, SI Ktena, C O’Brien, L Belli, A Schlaikjer, M Hardt
Proceedings of the National Academy of Sciences 119 (1), e2025334119, 2022
2742022
Faster gaze prediction with dense networks and fisher pruning
L Theis, I Korshunova, A Tejani, F Huszár
arXiv preprint arXiv:1801.05787, 2018
2252018
Adaptive Bayesian quantum tomography
F Huszár, NMT Houlsby
Physical Review A—Atomic, Molecular, and Optical Physics 85 (5), 052120, 2012
1942012
Is the deconvolution layer the same as a convolutional layer?
W Shi, J Caballero, L Theis, F Huszar, A Aitken, C Ledig, Z Wang
arXiv preprint arXiv:1609.07009, 2016
1832016
Super resolution using a generative adversarial network
W Shi, C Ledig, Z Wang, L Theis, F Huszar
US Patent 11,024,009, 2021
1552021
Note on the quadratic penalties in elastic weight consolidation
F Huszár
Proceedings of the National Academy of Sciences 115 (11), E2496-E2497, 2018
1552018
Collaborative Gaussian processes for preference learning
N Houlsby, F Huszar, Z Ghahramani, JM Hernández-lobato
Advances in Neural Information Processing Systems, 2096-2104, 2012
1542012
Variational inference using implicit distributions
F Huszár
arXiv preprint arXiv:1702.08235, 2017
1512017
Optimally-weighted herding is Bayesian quadrature
F Huszár, D Duvenaud
arXiv preprint arXiv:1204.1664, 2012
1062012
Training end-to-end video processes
Z Wang, RD Bishop, F Huszar, L Theis
US Patent 10,666,962, 2020
1052020
Experimental adaptive Bayesian tomography
KS Kravtsov, SS Straupe, R I. V., NMT Houlsby, H Ferenc, SP Kulik
Physical Review A 87 (6), 062122, 2013
982013
Approximate inference for the loss-calibrated Bayesian
S Lacoste–Julien, F Huszár, Z Ghahramani
Proceedings of the Fourteenth International Conference on Artificial …, 2011
902011
Stochastic outlier selection
J Janssens, F Huszár, E Postma, HJ van den Herik
Tilburg centre for Creative Computing, techreport 1, 2012, 2012
672012
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