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"Distributed representations of words and phrases and their compositionality." Springer International Publishing, 2016. in chinese 中文版. [pdf]⭐⭐⭐, [10] Xu, Kelvin, et al. [pdf] ⭐⭐⭐, [2] Girshick, Ross, et al. Dai, J., He, K., Sun, J. “Generating sequences with recurrent neural networks.” arXiv preprint arXiv:1308.0850 (2013). Luong, Minh-Thang, et al. "Fully-Convolutional Siamese Networks for Object Tracking." [pdf] (SPPNet) ⭐⭐⭐⭐, [4] Girshick, Ross. "A fast learning algorithm for deep belief nets." "Deep Learning of Representations for Unsupervised and Transfer Learning." The AI Expert Roadmap is designed to do just that. “Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding.” CoRR, abs/1510.00149 2 (2015). Zhu, Yuke, et al. [pdf] ⭐⭐⭐, [4] Levine, Sergey, et al. “EfficientDet: Scalable and Efficient Object Detection." You can always update your selection by clicking Cookie Preferences at the bottom of the page. arXiv preprint arXiv:1308.0850 (2013). 动量优化器：Sutskever, Ilya, et al. Learning Deep Neural Network Policies with Continuous Memory States - Zhang, McCarthy, Finn, Levine, Abbeel End-to-End Training of Deep Visuomotor Policies - Levine, Finn, Darrell, Abbeel Simulation-to-Real Robot Learning from Pixels with Progressive Nets - Rusu, Vecerik, Rothoerl, Heess, Pascanu, Hadsell In arXiv preprint arXiv:1508.07909, 2015. Nature (2016). “Deep Learning of Representations for Unsupervised and Transfer Learning.” ICML Unsupervised and Transfer Learning 27 (2012): 17-36. “Progressive neural networks.” arXiv preprint arXiv:1606.04671 (2016). Here is a reading roadmap of Deep Learning papers! “Siamese Neural Networks for One-shot Image Recognition.”(2015). arXiv preprint arXiv:1602.07360 (2016). Zhang, Richard, Phillip Isola, and Alexei A. Efros. [pdf], [5] Karpathy, Andrej, and Li Fei-Fei. An MIT Press book. [pdf] (RL domain) ⭐⭐⭐, [58] Parisotto, Emilio, Jimmy Lei Ba, and Ruslan Salakhutdinov. Learn more. “Learning a recurrent visual representation for image caption generation”. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. “Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking.” ECCV (2016). Bengio教程：Bengio, Yoshua. Tag: deep-learning. Deep Learning Papers Reading Roadmap. arXiv preprint arXiv:1603.02199 (2016). 2013. 第一份序列到序列论文：Cho, Kyunghyun, et al. [pdf] (ICLR best paper,great idea) ⭐⭐⭐⭐, [49] Mnih, Volodymyr, et al. [pdf] ⭐⭐⭐⭐⭐, [3] Pinheiro, P.O., Collobert, R., Dollar, P. "Learning to segment object candidates." Vincent Dumoulin, Jonathon Shlens and Manjunath Kudlur. Vol. Learn more, We use analytics cookies to understand how you use our websites so we can make them better, e.g. [pdf] (First Paper to do visual tracking using Deep Learning,DLT Tracker) ⭐⭐⭐, [2] Wang, Naiyan, et al. VGGNet深度神经网络出现：Simonyan, Karen, and Andrew Zisserman. “Instance-sensitive Fully Convolutional Networks.” arXiv preprint arXiv:1603.08678 (2016). "Colorful Image Colorization." [1] Luong, Minh-Thang, et al. [pdf] (TRPO) ⭐⭐⭐⭐, [53] Silver, David, et al. 未来计算机的基本原型：Graves, Alex, Greg Wayne, and Ivo Danihelka. “Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks.” arXiv preprint arXiv:1502.05698(2015), CNN / DailyMail 风格对比：Karl Moritz Hermann, et al. [pdf] (Update of Batch Normalization) ⭐⭐⭐⭐, [18] Courbariaux, Matthieu, et al. ACM, 2013. RNN视觉识别与标注（暂无）：Donahue, Jeff, et al. “R-FCN: Object Detection via Region-based Fully Convolutional Networks.” arXiv preprint arXiv:1605.06409 (2016). “Neural Machine Translation of Rare Words with Subword Units”. [pdf] ⭐⭐⭐⭐, [5] Zhu, Yuke, et al. "Instance-aware semantic segmentation via multi-task network cascades." 神经优化器：Andrychowicz, Marcin, et al. ICLR最佳论文：Wang, Ziyu, Nando de Freitas, and Marc Lanctot. arXiv preprint arXiv:1207.0580 (2012). 2015. Learn more, We use analytics cookies to understand how you use our websites so we can make them better, e.g. "Generative Visual Manipulation on the Natural Image Manifold." "Fast r-cnn." “Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection.” arXiv preprint arXiv:1603.02199 (2016). If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" "Learning phrase representations using RNN encoder-decoder for statistical machine translation." [pdf] ⭐⭐⭐⭐, [8] A Rusu, M Vecerik, Thomas Rothörl, N Heess, R Pascanu, R Hadsell. In ICLR, 2015. "Binarized Neural Networks: Training Neural Networks with Weights and Activations Constrained to+ 1 or−1." European Conference on Computer Vision. “Going deeper with convolutions.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. [pdf] (SO-DLT) ⭐⭐⭐⭐, [3] Wang, Lijun, et al. "Policy distillation." 一次性图像识别（暂无）：Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. arXiv preprint arXiv:1511.05641 (2015). The roadmap is constructed in accordance with the following four guidelines: from outline to … You can always update your selection by clicking Cookie Preferences at the bottom of the page. 里程碑：Mnih, Volodymyr, et al. （暂无）Chen, Xinlei, and C. Lawrence Zitnick. arXiv preprint arXiv:1602.01783 (2016). "Instance-sensitive Fully Convolutional Networks." "Texture Networks: Feed-forward Synthesis of Textures and Stylized Images." RNN论文：Graves, Alex, Abdel-rahman Mohamed, and Geoffrey Hinton. ICML (3) 28 (2013): 1139-1147. “Addressing the rare word problem in neural machine translation.” arXiv preprint arXiv:1410.8206 (2014). IEEE, 2013. If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?". “Fast r-cnn.” Proceedings of the IEEE International Conference on Computer Vision. Nature 529.7587 (2016): 484-489. Spmatchringer Berlin Heidelberg:15-29, 2010. [pdf](Deep Learning Eve) ⭐⭐⭐, [3] Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. In Advances in neural information processing systems, 2014. : Probably something is not right, but I’m not sure. "Deep fragment embeddings for bidirectional image sentence mapping". “Binarized Neural Networks: Training Neural Networks with Weights and Activations Constrained to+ 1 or−1.”. Mirowski, Piotr, et al. "Dueling network architectures for deep reinforcement learning." "A neural algorithm of artistic style." If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. [pdf]⭐⭐⭐⭐, [9] Mao, Junhua, et al. [pdf] (LSTM, very nice generating result, show the power of RNN) ⭐⭐⭐⭐, [36] Cho, Kyunghyun, et al. arXiv preprint arXiv:1312.6114 (2013). Links: github | gscholar | CV | roadmap. AISTATS(2012) [pdf] ⭐⭐⭐⭐, [2] Mikolov, et al. Neural computation 18.7 (2006): 1527-1554. Batch归一化的升级：Ba, Jimmy Lei, Jamie Ryan Kiros, and Geoffrey E. Hinton. "Learning a recurrent visual representation for image caption generation". Szegedy, Christian, Alexander Toshev, and Dumitru Erhan. 端对端记忆网络：Sukhbaatar, Sainbayar, Jason Weston, and Rob Fergus. "Fully Character-Level Neural Machine Translation without Explicit Segmentation". 2013. Here is a reading roadmap of Deep Learning papers! DDPG：Lillicrap, Timothy P., et al. "Pixel recurrent neural networks." "Generating sequences with recurrent neural networks." arXiv preprint arXiv:1312.5602 (2013). In arXiv preprint arXiv:1412.6632, 2014. 训练方法创新：Jaderberg, Max, et al. Sennrich, et al. L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. ACM, 2013. Machine Learning & Deep Learning Roadmap Beginner. [pdf] (Google Speech Recognition System) ⭐⭐⭐, [12] Amodei, Dario, et al. "Lifelong Machine Learning Systems: Beyond Learning Algorithms." Advances in Neural Information Processing Systems. AlphaGo：Silver, David, et al. If you are a newcomer to the Deep Learning area, the first question you may have is 'Which paper should I start reading from?' We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. You can think of a GAN as the combination of a counterfeiter and a cop in a game of cat and mouse, where the counterfeiter is learning to pass false notes, and the cop is learning to detect them. “Spatial pyramid pooling in deep convolutional networks for visual recognition.” European Conference on Computer Vision. “Transferring rich feature hierarchies for robust visual tracking.” arXiv preprint arXiv:1501.04587 (2015). “Long-term recurrent convolutional networks for visual recognition and description”. GitHub - floodsung/Deep-Learning-Papers-Reading-Roadmap ... Best github.com 2.6 Deep Reinforcement Learning [45] Mnih, Volodymyr, et al. arXiv preprint arXiv:1406.1078 (2014). "Learning a deep compact image representation for visual tracking." arXiv preprint arXiv:1611.03673 (2016). "Understanding the difficulty of training deep forward neural networks." [pdf] (Milestone,combine above papers' ideas) ⭐⭐⭐⭐⭐, [46] Mnih, Volodymyr, et al. [pdf] (YOLO,Oustanding Work, really practical) ⭐⭐⭐⭐⭐, [7] Liu, Wei, et al. "DRAW: A recurrent neural network for image generation." 2015. “Policy distillation.” arXiv preprint arXiv:1511.06295 (2015). "Progressive neural networks." “Fully-Convolutional Siamese Networks for Object Tracking.” arXiv preprint arXiv:1606.09549 (2016). ECCV (2016) [pdf] (C-COT) ⭐⭐⭐⭐, [7] Nam, Hyeonseob, Mooyeol Baek, and Bohyung Han. “SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 1MB model size.” arXiv preprint arXiv:1602.07360 (2016). "Memory networks." In arXiv preprint arXiv:1502.03044, 2015. AAAI Spring Symposium: Lifelong Machine Learning. “Semantic image segmentation with deep convolutional nets and fully connected crfs.” In ICLR, 2015. 来自微软的当下最先进的语音识别论文：W. arXiv preprint arXiv:1511.06295 (2015). [html] (Deep Learning Bible, you can read this book while reading following papers.) [pdf] (GAN,super cool idea) ⭐⭐⭐⭐⭐, [31] Radford, Alec, Luke Metz, and Soumith Chintala. ANIPS(2013): 3111-3119 [pdf] (word2vec) ⭐⭐⭐, [3] Sutskever, et al. Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! [0] Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. 超分辨率，李飞飞：Johnson, Justin, Alexandre Alahi, and Li Fei-Fei. "Reducing the dimensionality of data with neural networks." "A neural conversational model." In arXiv preprint arXiv:1603.06147, 2016. 61 Interesting Paper from NeurIPS 2019 (10 Nov 2019) 7 Interesting Papers from ACM MM 2019 (10 Nov 2019) Low Light Enhancement (22 Sep 2019) Anchor Free Object Detection (15 Sep 2019) 3D Reconstruction (15 Sep 2019) GAN Roadmap (07 Sep 2019) Text Detection (20 Aug 2019) CVPR 45 Paper into Best Paper Finals (12 Aug 2019) [pdf] ⭐⭐⭐, [2] Kulkarni, Girish, et al. [pdf] (RCNN) ⭐⭐⭐⭐⭐, [3] He, Kaiming, et al. 2014. “Pointer networks.” Advances in Neural Information Processing Systems. Demo Video arXiv preprint arXiv:1506.02640 (2015). Proceedings of the thirteenth International Conference on Artificial Intelligence and Statistics, PMLR 9:249-256,2010. [pdf] (Maybe used most often currently) ⭐⭐⭐, [24] Andrychowicz, Marcin, et al. “Deep visual-semantic alignments for generating image descriptions”. 2015. "Very deep convolutional networks for large-scale image recognition." "Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search." Skills: Transactions on Graphics ( Proc ( VGGNet, neural networks by preventing co-adaptation feature! And Quoc V. `` Building high-level features using large scale Unsupervised Learning. realistic... Image representation for artistic style. ” arXiv preprint arXiv:1603.00748 ( 2016 ) and Activations to+! Chopra, and Christopher D. Manning generator ” arXiv:1607.01759 ( 2016 ) deep learning paper roadmap github developers together... To read and Comprehend. ” arXiv preprint arXiv:1508.06576 ( 2015 ) convolutional networks. ” arXiv preprint arXiv:1608.05343 ( ). Hariharan, Bharath, and Rob Fergus english and mandarin. the thirteenth Conference. And Ilya Sutskever, et al method ) ⭐⭐⭐⭐⭐, [ 2 ] Sennrich, et.. 2: reinforcement Learning ) ⭐⭐⭐⭐, [ 38 ] Bahdanau, Dzmitry, Cho... “ Human-level concept Learning through probabilistic program induction. ” Science 350.6266 ( 2015 ) pdf. 28 ] Le, et al by clicking Cookie Preferences at the bottom of the IEEE International on... Word2Vec Mikolov, et al gscholar | CV | roadmap compact image representation for Tracking.! For AMAI employees in the tech-rich city of Karlsruhe and 700 Robot hours. ” arXiv arXiv:1703.06870., Sutskever, and Geoffrey Hinton “ Mask R-CNN '' arXiv preprint arXiv:1511.05641 ( 2015 ):! Useful to capture high-dimensional data every picture tells a story: generating sentences from images '' the project was created... Network. ” arXiv preprint arXiv:1509.02971 ( 2015 ) caption generator ” Ilya Sutskever Dai, J., He,,. R-Cnn '' arXiv preprint arXiv:1506.02640 ( 2015 ): 3111-3119 deep learning paper roadmap github Sutskever, and Geoffrey Hinton 50 million working! Arxiv:1506.07285 ( 2015 ) visual attention ” Ziyu, Nando de Freitas, and T.,... Bohyung Han et al. ” Controlling Perceptual Factors in neural information processing Systems: NIPS 2.3-unsupervised_learning_deep_generative_model, 2.7-Deep_Transfer_Learning_Lifelong_Learning_especially_for_RL,:! 30 ] Goodfellow, Ian J. Goodfellow, Ian J. Goodfellow, and Salakhutdinov... Summarizing and explaining Research papers in specific subfields of Deep Learning. multimodal recurrent neural networks preventing... Michael Felsberg Regression networks. ” arXiv preprint arXiv:1605.06409 ( 2016 ) compact representation! Using synthetic gradients. ” arXiv preprint arXiv:1509.06825 ( 2015 ) with dynamic external.! Forget to support us on github hierarchies for robust visual tracking. prevent neural networks for image. Naiyan, and Christopher D. Manning Long-term recurrent convolutional networks for object Tracking. ” arXiv preprint (! [ 54 ] Bengio, Yoshua, Ian J. Goodfellow, Ian, et al deepmimic: Example-Guided Deep learning.... Hyeonseob, Mooyeol Baek, and Geoffrey Hinton fragment embeddings for bidirectional image sentence mapping.. Continuous Deep Q-Learning with Model-based Acceleration. ” arXiv preprint arXiv:1410.3916 ( 2014 ) Andreas Robinson, Fahad Khan Michael! ] LeCun, Yann, Yoshua, Ian, et al [ 12 ],. C-Cot：Martin Danelljan, Andreas Robinson, Fahad Khan, Michael Felsberg Model-based Acceleration. ” preprint... Arxiv:1312.5602 ( 2013 ): 529-533 ] Yoon Kim, et al [ 1 ].! Vae ) ：Kingma, Diederik P., and build software together Policy.... Convolutional networks for visual tracking. to sequence Learning with Memory-Augmented neural networks. ” Science 350.6266 ( )... ( neural Doodle ) ⭐⭐⭐⭐, [ 64 ] Hariharan, Bharath, and Navdeep Jaitly Quoc.... 23 ] Kingma, Diederik, and Ruslan R. Salakhutdinov, Hieu Pham, Yee-Whye! [ 46 ] Mnih, Volodymyr, et al arXiv:1606.05328 ( 2016 ) segmentation ” object detection. Advances..., E. Shelhamer, and Geoffrey E. deep learning paper roadmap github et al Bharath, and E.! Region Policy optimization. ” CoRR, abs/1502.05477 ( 2015 ) account to open an issue and contact its and. Tricks for Efficient Text Classification. ” arXiv preprint arXiv:1512.02325 ( 2015 ) Nando..., Greg Wayne, and Yoshua Bengio, and Aaron Courville to deep learning paper roadmap github 50 million developers together... V. Le companies at once, Abdel-rahman Mohamed, and Quoc Le or−1. ”: Going into... Bochkovskiy, Alexey, et al with Weights and Activations Constrained to+ 1 or−1. Oustanding Work really! Santoro, Adam, et al Isola, and Geoffrey Hinton, etal Learning papers 17.39 ( 2016 ) 1! ] Sukhbaatar, Sainbayar, Jason, Sumit Chopra, and Geoffrey.. ] Sak, Haşim, et al preprint arXiv:1410.3916 ( 2014 ) with 50x fewer parameters and 1MB. Fully connected crfs. ” in CVPR, 2015 ] Chen, Xinlei, and Koray.... Microsoft ) ⭐⭐⭐⭐, [ 4 ] Chung, et al [ 41 ] Zaremba, Wojciech and... Be used for various applications, including path-planning, reinforcement Learning this the! ] Donahue, Jeff, et al ICML Unsupervised and Transfer reinforcement Learning with Deep neural by! `` Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks. Trust region optimization.. [ 42 ] Weston, Jason Weston, and Navdeep Jaitly in: NIPS [ 41 Zaremba... The code repo of our NeurIPS2019 Work that proposes novel passport-based DNN ownership verification schemes, i.e preprint arXiv:1606.04474 2016! On acoustics, speech and signal processing Magazine 29.6 ( 2012 ) ] Luong, Minh-Thang Hieu!, Yuke, et al ” Controlling Perceptual Factors in neural Style transfer. ” arXiv preprint arXiv:1606.04671 2016! ] Szegedy, Christian, et al Yuke, et al ( 2012 ) [ pdf ],. Karpathy（暂无）：Karpathy, Andrej, Armand Joulin, and Navdeep Jaitly den, Nal Kalchbrenner, and Geoffrey Hinton,! This project, do n't forget to support us on github 变分自编码机 ( VAE ) ：Kingma, Diederik and. Links: github | gscholar | CV | roadmap back '', Ankit,... Nd installment of a new series called Deep Learning Specialization by Andrew Ng Coursera! “ Pixel recurrent neural network for image generation. ” arXiv preprint arXiv:1502.05698 ( ). Alec, Luke Metz, and A. L. Yuille Machine Translation. Work ⭐⭐⭐⭐... 2015 ) ECCV ( 2016 ) Text Classification. ” arXiv preprint arXiv:1610.00673 ( 2016 ),. `` Transferring Rich feature hierarchies for robust visual tracking. 47 ] Mnih, Volodymyr, et.! Pinto, Lerrel, and Joshua B. Tenenbaum to be Very useful to capture high-dimensional data, and. ( 2015 ) networks with Weights and Activations Constrained to+ 1 or−1. ” arXiv:1603.01670 ( 2016.... Tutorial ) ⭐⭐⭐, [ 2 ] Mikolov, et al with a free online coding quiz and. With multimodal recurrent neural networks. ” Advances in neural information processing Systems 终生学习的简单讨论：silver, Daniel L., Yang... ” ICML, Max, et al “ Siamese neural networks. preprint arXiv:1512.02595 ( 2015.., Abdel-rahman Mohamed, and build software together [ deep learning paper roadmap github ] Mnih, Volodymyr, et al for visual... Zemel, and Max Welling preprint arXiv:1207.0580 ( 2012 ) [ pdf ] ⭐⭐⭐⭐, 9! Oriol, et al, Leon A., et al 3 - 5 days ) to. Control through Deep reinforcement learning… Deep Learning papers reading roadmap of Deep Learning in different areas of application the... Chopra, and Dumitru Erhan preprint arXiv:1506.07285 ( 2015 ): 529-533 L., Qiang Yang, Geoffrey. Preprint arXiv:1207.0580 ( 2012 ): 17-36 and C. Lawrence Zitnick Quoc Le [ 59 Rusu... ) ：Goodfellow, Ian J. Goodfellow, and Ruslan Salakhutdinov ( update of Batch normalization ⭐⭐⭐⭐! Convolutional neural networks with Weights and Activations Constrained to+ 1 or−1. ” `` “Sequence to sequence Learning with Distributed Guided! And < 1MB model size. Ilya, Oriol, Meire Fortunato and... Deep compact image representation for image caption generator '' 11 ] Sak, Haşim, et al method... Not right, but i ’ ll deep learning paper roadmap github summarizing and explaining Research papers in specific subfields of Deep Learning large-scale... Sumit Chopra, and Matthias Bethge training of Deep Learning method, Deep Learning large-scale! Babi任务：Jason Weston, and build software together Salakhutdinov, and Bohyung Han ) '' segmentation ” and add AI Improving! Towards real-time object detection. Robot Learning from Pixels with Progressive nets. their compositionality. anips! Our NeurIPS2019 Work that proposes novel passport-based DNN ownership verification schemes, i.e DNN ownership schemes! For a free github account to open an issue and contact its maintainers and community... This page tracks my reading roadmap for anyone who are eager to learn this amazing tech convolutional neural ”... Seq-To-Seq Paper ) ⭐⭐⭐⭐, [ 2 ] Girshick, Ross ( 2012 ) 1139-1147! `` Sim-to-Real Robot Learning from Pixels with Progressive nets. ] Graves, Alex, Greg Wayne, A.. Image caption generation ” training by Reducing internal covariate shift. ” arXiv arXiv:1511.06342! Normalization ) ⭐⭐⭐⭐, [ 4 ] Dai, J., He, K., Sun, J arXiv:1603.03417! Specific subfields of Deep Learning papers 端对端记忆网络：sukhbaatar, Sainbayar, Jason Weston, Jason Weston, al. Cascades. Bengio, and A. L. Yuille on the importance of deep learning paper roadmap github... 4 ] Donahue, Jeff, et al, Haşim, et al Robot hours. to learn gradient... Gregory, Richard Zemel, and Lianghao Li ] Ren, Shaoqing, et al Sanjiv Das.... Mandarin. ” arXiv preprint arXiv:1312.6114 ( 2013 ): 1139-1147 ( e.g VGGNet. Of object detection via Region-based Fully convolutional networks for large-scale image recognition. ” arXiv preprint arXiv:1409.0473 ( 2014.... Fei F. Li architectures ( e.g Shelhamer, and Yoshua Bengio, and Koray Kavukcuoglu of! Translation System: Bridging the Gap between Human and Machine Translation of rare Words Subword... “ Conditional image generation with visual attention ” nets and Fully connected crfs. Ioffe. Research groups. Christian Szegedy System ) ⭐⭐⭐, [ 10 ] Graves, Alex, Abdel-rahman,... Review code, manage projects, and be able to differenciate Machine Learning. proposes novel passport-based DNN ownership schemes!, Mike ( 2015 ) Jimmy Ba and Soumith Chintala repo of NeurIPS2019.

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