Fetching the paper…
Reading the bibliography…
This work details CipherGAN, an architecture inspired by CycleGAN used for inferring the underlying cipher mapping given banks of unpaired ciphertext and plaintext.
Brown corpus manual
W Nelson Francis and Henry Kucera · 1979
Earlier work this paper cites.
The automated cryptanalysis of substitution ciphers
John M Carroll and Steve Martin · 1986
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
Earlier work this paper cites.
Automated cryptanalysis of substitution ciphers
William S Forsyth and Reihaneh Safavi-Naini · 1993
Earlier work this paper cites.
An automated approach to solve simple substitution ciphers
RS Ramesh, G Athithan, and K Thiruvengadam · 1993
Earlier work this paper cites.
The Code Book: The Science of Secrecy from Ancient Egypt to Quantum Cryptography
Simon Singh · 2000
Earlier work this paper cites.
Solving substitution ciphers
Sam Hasinoff · 2003
Earlier work this paper cites.
Unsupervised analysis for decipherment problems
Kevin Knight, Anish Nair, Nishit Rathod, and Kenji Yamada · 2006
Earlier work this paper cites.
Genetic algorithm and tabu search attack on the mono-alphabetic substitution cipher i adhoc networks
AK Verma, Mayank Dave, and RC Joshi · 2007
Earlier work this paper cites.
Applying genetic algorithms for searching key-space of polyalphabetic substitution ciphers
Ragheb Toemeh and Subbanagounder Arumugam · 2008
Earlier work this paper cites.
Decipherment of substitution cipher using enhanced probability distribution
Bhadri Msvs Raju et al · 2010
Earlier work this paper cites.
The copiale cipher
Kevin Knight, Beáta Megyesi, and Christiane Schaefer · 2011
Earlier work this paper cites.
A cryptanalytic attack on vigenère cipher using genetic algorithm
SS Omran, AS Al-Khalid, and DM Al-Saady · 2011
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Cited alongside, same era.
Text understanding from scratch
Xiang Zhang and Yann LeCun · 2015
Cited alongside, same era.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
Cited alongside, same era.
Understanding and implementing cyclegan in tensorflow
Hardik Bansal and Archit Rathore · 2017
Later among the works it cites.
Maximum-likelihood augmented discrete generative adversarial networks
Tong Che, Yanran Li, Ruixiang Zhang, R Devon Hjelm, Wenjie Li, Yangqiu Song, and Yoshua Bengio · 2017
Later among the works it cites.
Many paths to equilibrium: Gans do not need to decrease a divergence at every step, 2017
William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, and Ian Goodfellow · 2017
Later among the works it cites.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
Later among the works it cites.
Boundary-seeking generative adversarial networks
R Devon Hjelm, Athul Paul Jacob, Tong Che, Kyunghyun Cho, and Yoshua Bengio · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
Cited alongside, same era.
Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
Cited alongside, same era.
Neural machine translation in linear time
Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, Aaron van den Oord, Alex Graves, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Gans for sequences of discrete elements with the gumbel-softmax distribution
Matt J Kusner and José Miguel Hernández-Lobato · 2016
Cited alongside, same era.
Semantic segmentation using adversarial networks
Pauline Luc, Camille Couprie, Soumith Chintala, and Jakob Verbeek · 2016
Cited alongside, same era.
The concrete distribution: A continuous relaxation of discrete random variables
Chris J Maddison, Andriy Mnih, and Yee Whye Teh · 2016
Cited alongside, same era.
Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley · 2016
Cited alongside, same era.
Later among the works it cites.
Naveen Kodali, Jacob Abernethy, James Hays, and Zsolt Kira · 2017
Later among the works it cites.
Unsupervised image-to-image translation networks
Ming-Yu Liu, Thomas Breuel, and Jan Kautz · 2017
Later among the works it cites.
tensorflow-cyclegan
Eyyüb Sari · 2017
Later among the works it cites.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Later among the works it cites.
Dualgan: Unsupervised dual learning for image-to-image translation
Zili Yi, Hao Zhang, Ping Tan Gong, et al · 2017
Later among the works it cites.
Seqgan: Sequence generative adversarial nets with policy gradient
Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Later among the works it cites.