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Deep generative models for graphs have shown great promise in the area of drug design, but have so far found little application beyond generating graph-structured molecules.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, Eero P Simoncelli, et al · 2004
Earlier work this paper cites.
Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Generating semantically precise scene graphs from textual descriptions for improved image retrieval
Sebastian Schuster, Ranjay Krishna, Angel Chang, Li Fei-Fei, and Christopher D Manning · 2015
Earlier work this paper cites.
Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Semantic segmentation of satellite images using deep learning, 2016
Shivaprakash Muruganandham · 2016
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
Earlier work this paper cites.
The world’s user-generated road map is more than 80% complete
Christopher Barrington-Leigh and Adam Millard-Ball · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Lukasz Kaiser, Aidan N Gomez, Noam Shazeer, Ashish Vaswani, Niki Parmar, Llion Jones, and Jakob Uszkoreit · 2017
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
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Road segmentation in sar satellite images with deep fully convolutional neural networks
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Spacenet: A remote sensing dataset and challenge series
Adam Van Etten, Dave Lindenbaum, and Todd M Bacastow · 2018
Cited alongside, same era.
Graphvae: Towards generation of small graphs using variational autoencoders
Martin Simonovsky and Nikos Komodakis · 2018
Cited alongside, same era.
State-of-the-art speech recognition with sequence-to-sequence models
Chung-Cheng Chiu, Tara N Sainath, Yonghui Wu, Rohit Prabhavalkar, Patrick Nguyen, Zhifeng Chen, Anjuli Kannan, Ron J Weiss, Kanishka Rao, Ekaterina Gonina, et al · 2018
Later among the works it cites.
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Łukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
Later among the works it cites.
Neural particle smoothing for sampling from conditional sequence models
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Road extraction from high-resolution remote sensing imagery using refined deep residual convolutional neural network
Lin Gao, Weidong Song, Jiguang Dai, and Yang Chen · 2019
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Ai is supercharging the creation of maps around the world [blog post. july 23, 2019]. retrieved from https://tech.fb.com, Jul 2019
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Molgan: An implicit generative model for small molecular graphs
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Learning deep generative models of graphs
Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, and Peter Battaglia · 2018
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Constrained graph variational autoencoders for molecule design
Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, and Alexander Gaunt · 2018
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Graphrnn: A deep generative model for graphs
Jiaxuan You, Rex Ying, Xiang Ren, William L Hamilton, and Jure Leskovec · 2018
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Graph r-cnn for scene graph generation
Jianwei Yang, Jiasen Lu, Stefan Lee, Dhruv Batra, and Devi Parikh · 2018
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Multi-objective de novo drug design with conditional graph generative model
Yibo Li, Liangren Zhang, and Zhenming Liu · 2018
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A generative model for electron paths
John Bradshaw, Matt J Kusner, Brooks Paige, Marwin HS Segler, and José Miguel Hernández-Lobato · 2018
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Xiaoming Gao, Christopher Klaiber, Drishtie Patel, and Jeff Underwood · 2019
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Deep generative models for generating labeled graphs
Shuangfei Fan and Bert Huang · 2019
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Efficient graph generation with graph recurrent attention networks
Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L Hamilton, David Duvenaud, Raquel Urtasun, and Richard S Zemel · 2019
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Neural turtle graphics for modeling city road layouts
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Path-augmented graph transformer network
Benson Chen, Regina Barzilay, and Tommi Jaakkola · 2019
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