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Deep Convolutional Neural Networks (DCNNs) is currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning.
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The pi-sigma network: An efficient higher-order neural network for pattern classification and function approximation
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From few to many: Illumination cone models for face recognition under variable lighting and pose
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A sigma-pi-sigma neural network (spsnn)
Chien-Kuo Li · 2003
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Polynomial neural networks architecture: analysis and design
Sung-Kwun Oh, Witold Pedrycz, and Byoung-Jun Park · 2003
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Ridge polynomial networks in pattern recognition
Christodoulos Voutriaridis, Yiannis S Boutalis, and Basil G Mertzios · 2003
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Training pi-sigma network by online gradient algorithm with penalty for small weight update
Yan Xiong, Wei Wu, Xidai Kang, and Chao Zhang · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Tensor decompositions and applications
Tamara G Kolda and Brett W Bader · 2009
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Predicting parameters in deep learning
Misha Denil, Babak Shakibi, Laurent Dinh, Marc’Aurelio Ranzato, and Nando De Freitas · 2013
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Analysis III: Spaces of Differentiable Functions
S.M. Nikol’skii · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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The cifar-10 dataset
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2014
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Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M Saxe, James L McClelland, and Surya Ganguli · 2014
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Learning both weights and connections for efficient neural network
Song Han, Jeff Pool, John Tran, and William Dally · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Deep learning in neural networks: An overview
Jürgen Schmidhuber · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Rupesh Kumar Srivastava, Klaus Greff, and Jürgen Schmidhuber · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Residual networks of residual networks: Multilevel residual networks
Ke Zhang, Miao Sun, Tony X Han, Xingfang Yuan, Liru Guo, and Tao Liu · 2017
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Learning hierarchical features from deep generative models
Shengjia Zhao, Jiaming Song, and Stefano Ermon · 2017
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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Chainer: a next-generation open source framework for deep learning
Seiya Tokui, Kenta Oono, Shohei Hido, and Justin Clayton · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Circnn: accelerating and compressing deep neural networks using block-circulant weight matrices
Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, et al · 2017
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Generating 3d faces using convolutional mesh autoencoders
Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, and Michael J Black · 2018
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On the convergence of adam and beyond
Sashank J Reddi, Satyen Kale, and Sanjiv Kumar · 2018
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Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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Feastnet: Feature-steered graph convolutions for 3d shape analysis
Nitika Verma, Edmond Boyer, and Jakob Verbeek · 2018
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Mixed link networks
Wenhai Wang, Xiang Li, Jian Yang, and Tong Lu · 2018
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Speech commands: A dataset for limited-vocabulary speech recognition
Pete Warden · 2018
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Sharing residual units through collective tensor factorization in deep neural networks
Chen Yunpeng, Jin Xiaojie, Kang Bingyi, Feng Jiashi, and Yan Shuicheng · 2018
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Neural 3d morphable models: Spiral convolutional networks for 3d shape representation learning and generation
Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Michael Bronstein, and Stefanos Zafeiriou · 2019
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Polygan: High-order polynomial generators
Grigorios Chrysos, Stylianos Moschoglou, Yannis Panagakis, and Stefanos Zafeiriou · 2019
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Implicit generation and generalization in energy-based models
Yilun Du and Igor Mordatch · 2019
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2019
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Non-adversarial image synthesis with generative latent nearest neighbors
Yedid Hoshen, Ke Li, and Jitendra Malik · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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On the expressive power of deep polynomial neural networks
Joe Kileel, Matthew Trager, and Joan Bruna · 2019
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Adversarial training of partially invertible variational autoencoders
Thomas Lucas, Konstantin Shmelkov, Karteek Alahari, Cordelia Schmid, and Jakob Verbeek · 2019
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Semantic image synthesis with spatially-adaptive normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, and Jun-Yan Zhu · 2019
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