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In most existing learning systems, images are typically viewed as 2D pixel arrays.
Convolutional networks for images, speech, and time series
Yann LeCun, Yoshua Bengio, et al · 1995
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The mnist database of handwritten digits
Y. LECUN · 1998
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Compositional pattern producing networks: A novel abstraction of development
Kenneth O Stanley · 2007
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 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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Rigid-motion scattering for image classification
Laurent Sifre and Stéphane Mallat · 2014
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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Spatial transformer networks
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Tensorizing neural networks
Alexander Novikov, Dmitrii Podoprikhin, Anton Osokin, and Dmitry P Vetrov · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Learning feed-forward one-shot learners
Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip Torr, and Andrea Vedaldi · 2016
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3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
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David Ha, Andrew Dai, and Quoc V Le · 2016
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Improved variational inference with inverse autoregressive flow
Durk P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
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Deconvolution and checkerboard artifacts
Augustus Odena, Vincent Dumoulin, and Chris Olah · 2016
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Branchynet: Fast inference via early exiting from deep neural networks
Surat Teerapittayanon, Bradley McDanel, and Hsiang-Tsung Kung · 2016
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Wasserstein generative adversarial networks
Martín Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Adrian Bulat and Georgios Tzimiropoulos · 2017
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Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, and David P Woodruff · 2017
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N Dauphin · 2017
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Non-autoregressive neural machine translation
Jiatao Gu, James Bradbury, Caiming Xiong, Victor OK Li, and Richard Socher · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Jae Hyun Lim and Jong Chul Ye · 2017
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Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley · 2017
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Masked autoregressive flow for density estimation
George Papamakarios, Theo Pavlakou, and Iain Murray · 2017
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Character-level language modeling with recurrent highway hypernetworks
Joseph Suarez · 2017
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Language modeling with recurrent highway hypernetworks
Joseph Suarez · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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On compressing deep models by low rank and sparse decomposition
Xiyu Yu, Tongliang Liu, Xinchao Wang, and Dacheng Tao · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Feature-wise transformations
Vincent Dumoulin, Ethan Perez, Nathan Schucher, Florian Strub, Harm de Vries, Aaron Courville, and Yoshua Bengio · 2018
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Approximating the predictive distribution via adversarially-trained hypernetworks
Christian Henning, Johannes von Oswald, João Sacramento, Simone Carlo Surace, Jean-Pascal Pfister, and Benjamin F Grewe · 2018
HyperGAN: A generative model for diverse, performant neural networks
Neale Ratzlaff and Li Fuxin · 2019
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Deepvoxels: Learning persistent 3d feature embeddings
Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Nießner, Gordon Wetzstein, and Michael Zollhofer · 2019
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Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhoefer, and Gordon Wetzstein · 2019
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Spatial broadcast decoder: A simple architecture for learning disentangled representations in vaes
Nicholas Watters, Loic Matthey, Christopher P Burgess, and Alexander Lerchner · 2019
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Efficient, lightweight, coordinate-based network for image super resolution
K. Zafeirouli, A. Dimou, A. Axenopoulos, and P. Daras · 2019
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Neural autoregressive flows
Chin-Wei Huang, David Krueger, Alexandre Lacoste, and Aaron Courville · 2018
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An intriguing failing of convolutional neural networks and the coordconv solution
Rosanne Liu, Joel Lehman, Piero Molino, Felipe Petroski Such, Eric Frank, Alex Sergeev, and Jason Yosinski · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 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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Parallel wavenet: Fast high-fidelity speech synthesis
Aaron Oord, Yazhe Li, Igor Babuschkin, Karen Simonyan, Oriol Vinyals, Koray Kavukcuoglu, George Driessche, Edward Lockhart, Luis Cobo, Florian Stimberg, et al · 2018
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Graph hypernetworks for neural architecture search
Chris Zhang, Mengye Ren, and Raquel Urtasun · 2019
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Image generators with conditionally-independent pixel synthesis
Ivan Anokhin, Kirill Demochkin, Taras Khakhulin, Gleb Sterkin, Victor Lempitsky, and Denis Korzhenkov · 2020
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pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
Eric R Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2020
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Principled weight initialization for hypernetworks
Oscar Chang, Lampros Flokas, and Hod Lipson · 2020
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Dynamic convolution: Attention over convolution kernels
Yinpeng Chen, Xiyang Dai, Mengchen Liu, Dongdong Chen, Lu Yuan, and Zicheng Liu · 2020
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Structured multi-hashing for model compression
Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, and Miguel A. Carreira-Perpinan · 2020
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Comparing the parameter complexity of hypernetworks and the embedding-based alternative
Tomer Galanti and Lior Wolf · 2020
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On the modularity of hypernetworks
Tomer Galanti and Lior Wolf · 2020
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Low-rank compression of neural nets: Learning the rank of each layer
Yerlan Idelbayev and Miguel A. Carreira-Perpinan · 2020
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Msg-gan: Multi-scale gradients for generative adversarial networks
Animesh Karnewar and Oliver Wang · 2020
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Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Grasping field: Learning implicit representations for human grasps
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Adversarial generation of continuous implicit shape representations
Marian Kleineberg, Matthias Fey, and Frank Weichert · 2020
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On the optimization dynamics of wide hypernetworks
Etai Littwin, Tomer Galanti, and Lior Wolf · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Hypervae: A minimum description length variational hyper-encoding network
Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, and Svetha Venkatesh · 2020
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Hcnaf: Hyper-conditioned neural autoregressive flow and its application for probabilistic occupancy map forecasting
Geunseob Oh and Jean-Sebastien Valois · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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Deep learning needs a prefrontal cortex
Jacob Russin, Randall O’Reilly, and Yoshua Bengio · 2020
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Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien N.P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein · 2020
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Hybridpose: 6d object pose estimation under hybrid representations
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Fourier features let networks learn high frequency functions in low dimensional domains
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Continual learning with hypernetworks
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Solov2: Dynamic, faster and stronger
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Castle in the sky: Dynamic sky replacement and harmonization in videos
Zhengxia Zou · 2020
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