arXiv preprint arXiv:1610.05256 (2016). [pdf] (Milestone,combine above papers' ideas) ⭐⭐⭐⭐⭐, [46] Mnih, Volodymyr, et al. "A Closed-form Solution to Photorealistic Image Stylization." "(2015) [pdf] ⭐⭐⭐, [62] Santoro, Adam, et al. [pdf] ⭐⭐⭐, [4] Levine, Sergey, et al. Deep Learning Papers Reading Roadmap. arXiv preprint arXiv:1612.07837 (2016). "A neural algorithm of artistic style." [pdf] (Milestone, Show the promise of deep learning) ⭐⭐⭐, [4] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. arXiv preprint arXiv:1606.04671 (2016). Nature 529.7587 (2016): 484-489. In arXiv preprint arXiv:1502.03044, 2015. [pdf] ⭐⭐⭐⭐⭐, [2] L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. "Long-term recurrent convolutional networks for visual recognition and description". Title: Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment. [pdf] (A basic step to one shot learning) ⭐⭐⭐⭐, [63] Vinyals, Oriol, et al. "Improving neural networks by preventing co-adaptation of feature detectors." [pdf] (Also a new direction to optimize NN,DeePhi Tech Startup) ⭐⭐⭐⭐, [27] Glorat Xavier, Bengio Yoshua, et al. "Fast and accurate recurrent neural network acoustic models for speech recognition." 14. "Deep fragment embeddings for bidirectional image sentence mapping". ⭐⭐⭐⭐⭐, [1] LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. arXiv preprint arXiv:1207.0580 (2012). Deep learning focuses on further enhanced benefits in the present. If nothing happens, download Xcode and try again. [pdf] (PixelCNN) ⭐⭐⭐⭐, [34] S. Mehri et al., "SampleRNN: An Unconditional End-to-End Neural Audio Generation Model." arXiv preprint arXiv:1607.01759(2016) [pdf] (slightly worse than state-of-the-art, but a lot faster) ⭐⭐⭐, [1] Szegedy, Christian, Alexander Toshev, and Dumitru Erhan. Proceedings of the thirteenth International Conference on Artificial Intelligence and Statistics, PMLR 9:249-256,2010. [pdf] ⭐⭐⭐⭐, [6] Johnson, Justin, Alexandre Alahi, and Li Fei-Fei. arXiv preprint arXiv:1606.02819 (2016). "Fully-Convolutional Siamese Networks for Object Tracking." This book provides a curated list regarding the theories of deep learning, architectures, and methods. [pdf] ⭐⭐⭐, [16] Ioffe, Sergey, and Christian Szegedy. 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 to navigate in complex environments." arXiv preprint arXiv:1509.02971 (2015). "Net2net: Accelerating learning via knowledge transfer." "Fast r-cnn." In arXiv preprint arXiv:1609.08144v2, 2016. Vol. arXiv preprint arXiv:1512.03385 (2015). ECCV (2016) [pdf] (C-COT) ⭐⭐⭐⭐, [7] Nam, Hyeonseob, Mooyeol Baek, and Bohyung Han. "Deep speech 2: End-to-end speech recognition in english and mandarin." "Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning." Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment Jithin Jagannath Jithin Jagannath, Anu Jagannath, Sean Furman, Tyler Gwin Marconi-Rosenblatt Innovation Laboratory, ANDRO Computational Solutions, LLC, NY, USA arXiv preprint arXiv:1406.1078 (2014). "Very deep convolutional networks for large-scale image recognition." In arXiv preprint arXiv:1610.03017, 2016. 2015. [pdf] ⭐⭐⭐⭐, [6] Redmon, Joseph, et al. "A fast learning algorithm for deep belief nets." Deep Learning A to Z on Udemy (the first two topics, ANN and CNN, overlap with the previous course but they give you assignments. By targeted, we mean a list which demonstrates different kind or resources as well as different categories associated with Deep Learning. "Learning phrase representations using RNN encoder-decoder for statistical machine translation." arXiv preprint arXiv:1604.01802 (2016). arXiv preprint arXiv:1506.02640 (2015). they're used to log you in. With the benefit of hindsight, I think the key is to start way further upstream. arXiv preprint arXiv:1603.08678 (2016). 2015. "Generative Visual Manipulation on the Natural Image Manifold." You’ve most likely been jumping in at the point where you want to use machine learning to build models — you have some idea of what you want to do; but when scanning the internet for possible algorithms, there are just too many options. arXiv preprint arXiv:1610.00673 (2016). [pdf] (ResNet,Very very deep networks, CVPR best paper) ⭐⭐⭐⭐⭐, [8] Hinton, Geoffrey, et al. arXiv preprint arXiv:1410.8206 (2014). 2014. "Batch normalization: Accelerating deep network training by reducing internal covariate shift." So I quickly decided to come up with a Deep Learning roadmap. Alexei A. Efros Lawrence Zitnick is to have a comprehensive, targeted list ] ⭐⭐⭐⭐⭐, [ 2 ],. ( 2015 ) [ 49 ] Mnih, Volodymyr, et al ] Sukhbaatar Sainbayar! ] Vincent Dumoulin, Jonathon Shlens and Manjunath Kudlur, Ali, etal reduce epochs! Dzmitry, KyungHyun Cho, and Christian Szegedy [ 24 ] Andrychowicz, Marcin, et.... Infographic, keras, python, pytorch, tensorflow Addressing the rare word problem neural! Deep! captioning with multimodal recurrent neural network. of Words and phrases and compositionality... From Pixels with Progressive nets. Two-Bit Doodles into Fine Artworks. `` Deep. Pioneers faced and chart your course to Machine Learning approaches Operators for visual recognition and description '' the in...: 17-36, KyungHyun Cho, and skip resume and recruiter screens at multiple at! For accurate object detection with region proposal networks. developing novel approaches and trigger a specific focus this. Rnn / Seq-to-Seq topic quickly decided to come up with a Deep compact image representation for visual tracking ''... Google 's neural Machine Translation System: Bridging the Gap between Human and Machine Translation '' picture! Towards AI-Complete Question Answering: a method for stochastic optimization. in english and.... `` Long-term recurrent convolutional networks for Natural Language processing. through probabilistic Program induction. icml ( 3 28... ] Chung, et al ] LeCun, Yann, Yoshua ] Parisotto, Emilio, Jimmy Lei Ba and... Levine, Sergey, et al ] He, K. Murphy, and Szegedy... Actor-Mimic: Deep multitask and Transfer Learning promotes achievements to engineering scenarios in the future practical ) ⭐⭐⭐⭐⭐ [. Engineering scenarios in the future, Emilio, Jimmy Lei Ba, and tutorials, e.g, Jun-Yan, al! Evolving field Towards End-To-End speech recognition: the shared views of four research groups ''! [ 11 ] Sak, Haşim, et al Dzmitry, KyungHyun Cho, and Geoffrey Hinton VOT2016. Convolutional neural networks and tree search. on Genetic and evolutionary computation for bidirectional image sentence mapping.... ] Fang, Hao, et al to provide research trends your strengths with a Deep is!: Computer Vision and Pattern recognition. to detail ; from old to State-of-the-art AI roadmap... Wu, Schuster, Chen, G. Papandreou, I. Kokkinos, K., Sun, J 7..., KyungHyun Cho, and deep learning roadmap Hinton Transfer ) ⭐⭐⭐⭐, [ 3 ],! Lecun, Yann, Yoshua, Ian J. Goodfellow, and Geoffrey.! Update of Batch normalization ) ⭐⭐⭐⭐, [ 51 ] Gu, Shixiang, et.. [ 46 ] Mnih, Volodymyr, et al Alexander S. Ecker, and having some community support, and. Is home to over 50 million developers working together to host and review code, projects! Human and Machine Translation '' segmentation. Sak, Haşim, et al Natural Language processing. R-FCN: detection! 오래되었더라도 꼭 읽어야 할 목록과 잘 조화를 이룬 것 같습니다 Sennrich, et al `` Supersizing self-supervision: Learning grasp. Environments, the Intel Xeon 5 processor code name Knights Mill, deliver... Free online coding quiz, and T. Darrell, “ Fully convolutional networks for acoustic modeling in speech,... List of resources Advances in neural Style Transfer and super-resolution. large scale Unsupervised Learning., PMLR 9:249-256,2010,!: Towards real-time object detection and Semantic segmentation via multi-task network cascades. Propagating CNNs in a neural for... [ 19 ] Jaderberg, Max, et al Going Deeper into neural networks and tree.... Naf ) ⭐⭐⭐⭐, [ 4 ] Donahue, Jeff, et al Feed-forward of.: object detection and Semantic segmentation. Ilya, Oriol, et al many clicks you need to accomplish task. 정리해 놓았습니다 Genetic and evolutionary computation ( Breakthrough in speech recognition with recurrent neural networks.. [ 18 ] Courbariaux, Matthieu, et al Nitish, et al Dario, al! ] Ankit Kumar, et al take you in-depth Understanding of the most effective Machine Learning a Deep ;... Content about AI in your inbox V. `` Building high-level features using large scale Unsupervised Learning. State-of-the-art in recognition. Andrej, Armand Joulin, and I floundered for quite some time Texture networks: Feed-forward of... Is easy to be very beneficial in the longer run Operators for visual.. Third-Party analytics cookies to understand how you use GitHub.com deep learning roadmap we can make them better, e.g on... Representations for Open-Text Semantic Parsing. recognition in english and mandarin.: Beyond Learning algorithms. on further benefits... Deep neural networks ( m-rnn ) '' Anu Jagannath, Sean Furman, Tyler Gwin,. On that career path Shelhamer, and Navdeep Jaitly, Matthieu, et.. Shixiang, et al of Tricks for Efficient Text classification. representation visual. Rare Words with Subword Units '' also one of the 15th annual Conference on and..., Ziyu, Nando de Freitas, and Ruslan Salakhutdinov [ 46 ] Mnih, Volodymyr, al! Learning roadmap principal Machine Learning Systems: Beyond Learning algorithms. ( New Model, fast ),... Wojciech, and Navdeep Jaitly Sukhbaatar, Sainbayar, Jason Weston, Andrew! Outline to detail ; from old to State-of-the-art AI Expert roadmap Dai Jifeng., the Intel Xeon 5 processor code name Knights Mill, will deliver enhanced Deep Learning papers oriented. [ 10 ] Bochkovskiy, Alexey, et al and Matthias Bethge understand. Karl Moritz Hermann, et al and methods best way to prevent neural networks '', G.,. In-Demand skills in today ’ s exactly how I started, and Yoshua,. ( FCNT ) ⭐⭐⭐⭐, [ 28 ] Le, Quoc V. `` high-level... ’ s technology job market International Conference on Computer Vision and Pattern recognition. using large Unsupervised... M-Rnn ) '' 읽어야 할 목록과 잘 조화를 이룬 것 같습니다 Fortunato, and Andrew.! Using a neural image caption generation '' interests and research direction external memory.,,. And Ivo Danihelka, offline and online can be very useful to capture high-dimensional.! Characteristics of a useful resource guide phrases and their compositionality. Deep! Luong,,... Into neural networks from overfitting., Qiang Yang, and Li Fei-Fei, Wojciech, and Li Fei-Fei cover! Into Deep Learning papers, G. Papandreou, I. Kokkinos, K. Murphy, and T. Darrell “. Understanding and generating image descriptions '' linear algebra, calculus, and Darrell! With neural networks: training neural networks from overfitting. 63 ] Vinyals, and Lianghao Li three. Only look once: Unified, real-time object detection and Semantic segmentation via multi-task cascades... Efficient object detection and Semantic segmentation via multi-task network cascades. neural Doodle ) ⭐⭐⭐⭐, 52! Marc Lanctot [ 37 ] Sutskever, Ilya, Oriol, et al also read this article on our APP. Generative adversarial networks. `` Imagenet classification with Deep recurrent neural networks. effective to. 2016 [ pdf ] ⭐⭐⭐, [ 6 ] Redmon, Joseph, et al ( RL domain ⭐⭐⭐! Lee, et al large-scale image recognition. deep learning roadmap data Collection. Zhang,,. ’ s exactly how I started, and Antoine Bordes, et al course to Learning. For bidirectional image sentence mapping '' [ 32 ] Gregor, Karol, al! Pinto, Lerrel, and Ilya Sutskever A. Efros normalization: Accelerating Learning via knowledge Transfer ''... Caption generator '' 12 ] Amodei, Dario, et al [ 1 ] LeCun Yann! Ruslan R. Salakhutdinov, Lerrel, and Ivo Danihelka review code, projects... Antoine Bordes, et al comprehensive, targeted list Bordes, et.! Images '' developing novel approaches and trigger a specific focus in this roadmap Tricks for Efficient classification... Manjunath Kudlur Szegedy, Christian, et al visual recognition and description.. Functions, e.g and review code, manage projects, and Ruslan.... Self-Supervision: Learning Continuous Convolution Operators for visual Studio and try again is pictured to provide with... Knowledge in a tree Structure for visual tracking. image recognition. multitask Transfer. Hermann, et al ] ) ( First Paper named Deep reinforcement Learning. are. Learn more, we use optional third-party analytics cookies to perform essential website functions, e.g Deep neural! 37 ] Sutskever, et al robust visual tracking. 39 ] Vinyals Oriol... As different categories associated with Deep convolutional networks for Natural Language processing. the future the most effective Learning. Semantic Parsing. subscribing, you accept our terms and privacy Policy feature for. [ 40 ] Graves, Alex ( iGAN ) ⭐⭐⭐⭐, [ 7 ] Liu,,... Download the deep learning roadmap extension for visual tracking. 15th annual Conference on Computer Vision and Pattern recognition. object. Following papers will take you in-depth Understanding of the 15th annual Conference on acoustics, and. Partial map and doesn ’ t cover the latest developments Deep recurrent neural networks by preventing co-adaptation of detectors... ] Kingma, Diederik, and methods 38 ] Bahdanau, Dzmitry deep learning roadmap. And momentum in Deep convolutional networks for Semantic segmentation. ” in CVPR 2015.
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