[pdf] ⭐⭐⭐, [16] Ioffe, Sergey, and Christian Szegedy. [pdf] ⭐⭐⭐⭐, [1] Wang, Naiyan, and Dit-Yan Yeung. European Conference on Computer Vision. arXiv preprint arXiv:1507.06947 (2015). arXiv preprint arXiv:1506.03340(2015) [pdf] (CNN/DailyMail cloze style questions) ⭐⭐, [8] Alexis Conneau, et al. The roadmap is constructed in accordance with the following four guidelines: [pdf] (RL domain) ⭐⭐⭐, [57] Parisotto, Emilio, Jimmy Lei Ba, and Ruslan Salakhutdinov. [pdf] ⭐⭐⭐⭐, [6] Yahya, Ali, et al. The roadmap is constructed in accordance with the following four guidelines: You will find many papers that are quite new but really worth reading. arXiv preprint arXiv:1610.05256 (2016). [pdf] (Milestone, Show the promise of deep learning) ⭐⭐⭐, [4] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. [1] Sutskever, Ilya, et al. AAAI Spring Symposium: Lifelong Machine Learning. 2013 IEEE international conference on acoustics, speech and signal processing. ICML Unsupervised and Transfer Learning 27 (2012): 17-36. [pdf] (Baidu Speech Recognition System) ⭐⭐⭐⭐, [13] W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig "Achieving Human Parity in Conversational Speech Recognition." "Adam: A method for stochastic optimization. Neural computation 18.7 (2006): 1527-1554. arXiv preprint arXiv:1610.04286 (2016). An MIT Press book. Advances in neural information processing systems. Advances in Neural Information Processing Systems. "Evolving large-scale neural networks for vision-based reinforcement learning." 2013 IEEE international conference on acoustics, speech and signal processing. "Matching Networks for One Shot Learning." "Playing atari with deep reinforcement learning." "A fast learning algorithm for deep belief nets." After reading above papers, you will have a basic understanding of the Deep Learning history, the basic architectures of Deep Learning model(including CNN, RNN, LSTM) and how deep learning can be applied to image and speech recognition issues. [pdf] ⭐⭐⭐⭐, [2] Sennrich, et al. 7 min read. "Imagenet classification with deep convolutional neural networks." We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. [pdf] (Modify previously trained network to reduce training epochs) ⭐⭐⭐, [22] Sutskever, Ilya, et al. "(2015) [pdf] ⭐⭐⭐, [61] Santoro, Adam, et al. Learn more. "Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing." Here is a reading roadmap of Deep Learning papers! If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" arXiv preprint arXiv:1508.06576 (2015). "Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection." arXiv preprint arXiv:1312.6114 (2013). ), [6] Szegedy, Christian, et al. "ICML (3) 28 (2013): 1139-1147. Some milestone papers are listed in RNN / Seq-to-Seq topic. "Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks." Unmanned Aerial Systems (UAS) are being increasingly deployed for commercial, civilian, and military applications. 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. "On the importance of initialization and momentum in deep learning." [pdf] ⭐⭐⭐, [63] Hariharan, Bharath, and Ross Girshick. 2013. It is considered to be very useful to capture high-dimensional data. If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" arXiv preprint arXiv:1508.04025 (2015). I found a pretty good deep learning papers roadmap that went chronologically through the main papers from the main ML categories. Last time out we looked at Booking.comâs lessons learned from introducing machine learning to their product stack. [pdf] ⭐⭐⭐⭐, [9] He, Gkioxari, et al. [pdf] ⭐⭐⭐, [2] Girshick, Ross, et al. [pdf] (RNN), [10] Graves, Alex, and Navdeep Jaitly. "End-to-end memory networks." The Ultimate Guide to Data Engineer Interviews, Change the Background of Any Video with 5 Lines of Code, Get KDnuggets, a leading newsletter on AI, [html] (Deep Learning Bible, you can read this book while reading following papers.) arXiv preprint arXiv:1410.5401 (2014). This directory and the files within it may be erased once retrieval completes. arXiv preprint arXiv:1610.05256 (2016). [pdf](Deep Learning Eve) ⭐⭐⭐, [3] Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. [pdf] (RCNN) ⭐⭐⭐⭐⭐, [3] He, Kaiming, et al. "Generating sequences with recurrent neural networks." [pdf] (PixelCNN) ⭐⭐⭐⭐, [34] Graves, Alex. songrotek/Deep-Learning-Papers-Reading-Roadmap Oct-21-2016, 12:41:05 GMT â #artificialintelligence If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" arXiv preprint arXiv:1606.02819 (2016). [pdf] (Three Giants' Survey) ⭐⭐⭐⭐⭐, [2] Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh. [pdf] ⭐⭐⭐⭐, [6] Redmon, Joseph, et al. Note: the file github.com-songrotek-Deep-Learning-Papers-Reading-Roadmap_-_2017-06-26_10-24-53_meta.xml contains metadata about this torrent's contents. 2016 [pdf] ⭐⭐⭐, [5] Dai, J., He, K., Sun, J. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Awesome Deep Learning Papers is a bit outdated (the last update was made two years ago) but it does list the most cited papers from 2012â2016, sorted by discipline, such as convolutional neural network models, optimization techniques, object detection, and reinforcement learning. "Generative Visual Manipulation on the Natural Image Manifold." "Spatial pyramid pooling in deep convolutional networks for visual recognition." "Actor-mimic: Deep multitask and transfer reinforcement learning." Springer Berlin Heidelberg:15-29, 2010. ICML (3) 28 (2013): 1139-1147. [pdf] (NAF) ⭐⭐⭐⭐, [51] Schulman, John, et al. I also believe that the mathematics behind some of these papers can be very difficult, so you can skip those parts if you don’t feel comfortable with them. [pdf] (Godfather's Work) ⭐⭐⭐⭐, [56] Rusu, Andrei A., et al. You can always update your selection by clicking Cookie Preferences at the bottom of the page. "Show, attend and tell: Neural image caption generation with visual attention". In arXiv preprint arXiv:1411.4555, 2014. [pdf] (control style transfer over spatial location,colour information and across spatial scale)⭐⭐⭐⭐, [9] Ulyanov, Dmitry and Lebedev, Vadim, et al. [pdf] (State-of-the-art in speech recognition, Microsoft) ⭐⭐⭐⭐. arXiv preprint arXiv:1602.07360 (2016). "Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours." "Controlling Perceptual Factors in Neural Style Transfer." Deep Learning Papers Reading Roadmap - Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech. "Addressing the rare word problem in neural machine translation." Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! "Very deep convolutional networks for large-scale image recognition." "Neural Machine Translation of Rare Words with Subword Units". I completed this last March and it was great. Advances in neural information processing systems. Here is a reading roadmap of Deep Learning papers! "Learning phrase representations using RNN encoder-decoder for statistical machine translation." "Auto-encoding variational bayes." arXiv preprint arXiv:1512.02595 (2015). [pdf] (Three Giants' Survey), [2] Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh. Reading/Implementing papers); I don't really know the "engineering" side of things but would like to pick these skills up on my spare time. they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. After reading above papers, you will have a basic understanding of the Deep Learning history, the basic architectures of Deep Learning model(including CNN, RNN, LSTM) and how deep learning can be applied to image and speech recognition issues. [pdf]⭐⭐⭐⭐, [7] Fang, Hao, et al. In arXiv preprint arXiv:1609.08144v2, 2016. arXiv preprint arXiv:1601.06759 (2016). 2015. [pdf] ⭐⭐⭐⭐, [1] Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015). "Pointer networks." Vol. "Towards End-To-End Speech Recognition with Recurrent Neural Networks." "Speech recognition with deep recurrent neural networks." 2015. Deep Learning Papers Reading Roadmap github.com. "Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups." Here is a reading roadmap of Deep Learning papers! You will find many papers that are quite new but really worth reading. "Going deeper with convolutions." arXiv preprint arXiv:1603.03417(2016). [pdf] (A step to large data) ⭐⭐⭐⭐, [1] Antoine Bordes, et al. The current UAS state-of-the-art still depends on a remote human controller with robust wireless links to perform several of these applications. In Advances in neural information processing systems, 2014. By subscribing you accept KDnuggets Privacy Policy, pythonprogramming.net/neural-networks-machine-learning-tutorial, original for the full listing of papers and categories, Top 20 Recent Research Papers on Machine Learning and Deep Learning, Awesome Deep Learning: Most Cited Deep Learning Papers, A Rising Library Beating Pandas in Performance, 10 Python Skills They Donât Teach in Bootcamp. [0] Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. [pdf] ⭐⭐⭐⭐, [7] Gu, Shixiang, et al. ANIPS(2013): 3111-3119 [pdf] (word2vec) ⭐⭐⭐, [3] Sutskever, et al. "Lifelong Machine Learning Systems: Beyond Learning Algorithms." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015. Machine-learning systems are used to identify objects in images, transcribe speech into text, match news items, posts or products with usersâ interests, and select relevant results of search. In arXiv preprint arXiv:1412.2306, 2014. ⭐⭐⭐⭐⭐, [1] LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. [pdf]⭐⭐⭐⭐, [9] Mao, Junhua, et al. arXiv preprint arXiv:1609.05143 (2016). [pdf]⭐⭐⭐⭐⭐. "Character-Aware Neural Language Models." arXiv preprint arXiv:1312.5602 (2013). Before this list, there exist other awesome deep learning lists, for example, Deep Vision and Awesome Recurrent Neural Networks. [pdf] (AlphaGo) ⭐⭐⭐⭐⭐, [53] Bengio, Yoshua. "Mastering the game of Go with deep neural networks and tree search." "Fast and accurate recurrent neural network acoustic models for speech recognition." The Practical Importance of Feature Selection - Jun 12, 2017. arXiv preprint arXiv:1506.02640 (2015). [pdf] (DDPG) ⭐⭐⭐⭐, [50] Gu, Shixiang, et al. [pdf] (ResNet,Very very deep networks, CVPR best paper) ⭐⭐⭐⭐⭐, [8] Hinton, Geoffrey, et al. [pdf] (State-of-the-art method) ⭐⭐⭐⭐⭐, [49] Lillicrap, Timothy P., et al. Nature 521.7553 (2015): 436-444. arXiv preprint arXiv:1611.07865 (2016). [pdf] ⭐⭐⭐, [4] Levine, Sergey, et al. ANIPS(2014) [pdf] ⭐⭐⭐, [4] Ankit Kumar, et al. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 1MB model size." "Low-shot visual object recognition." [pdf] (ICLR best paper,great idea) ⭐⭐⭐⭐, [48] Mnih, Volodymyr, et al. It is definitely hard to keep up with the research. Learn an Effective Lip Reading Model without Pains. [pdf] (iGAN) ⭐⭐⭐⭐, [4] Champandard, Alex J. [pdf]⭐⭐⭐⭐⭐, [6] Wu, Schuster, Chen, Le, et al. "Pixel recurrent neural networks." Papers Reading Roadmap Introduction. "Network Morphism." But the question remains where to start. 2015. The roadmap is constructed in accordance with the following four guidelines: Machine Learning A to Z on Udemy. "Learning a recurrent visual representation for image caption generation". Editor: What follows is a portion of the papers from this list. [pdf] ⭐⭐⭐, [2] Levine, Sergey, et al. "Inceptionism: Going Deeper into Neural Networks". Deep-Learning-Papers-Reading-Roadmap. [pdf] ⭐⭐⭐⭐, [8] A Rusu, M Vecerik, Thomas Rothörl, N Heess, R Pascanu, R Hadsell. Here is a reading roadmap of Deep Learning papers! If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?". "Neural Machine Translation by Jointly Learning to Align and Translate." Docs » Papers; Edit on GitHub; Papers¶ This chapter is associated with the papers published in deep learning. Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. arXiv preprint arXiv:1512.02595 (2015). "Adam: A method for stochastic optimization." "Deep learning." arXiv preprint arXiv:1507.06947 (2015). Reading for the purpose of understanding is not done through one pass of the contents within the paper. arXiv.org. "Perceptual losses for real-time style transfer and super-resolution." The following papers will take you in-depth understanding of the Deep Learning method, Deep Learning in different areas of application and the frontiers. "Modeling and Propagating CNNs in a Tree Structure for Visual Tracking." "Colorful Image Colorization." The lack of autonomy restricts the domains of application and tasks for which a UAS can be deployed. [pdf] (YOLO,Oustanding Work, really practical) ⭐⭐⭐⭐⭐, [7] Liu, Wei, et al. "Effective approaches to attention-based neural machine translation." Nature 518.7540 (2015): 529-533. Letâs deep dive into each step and see what all ... Donât start reading maths book until and unless you are not in rush to ... Neural Network and Deep Learning. ECCV (2016) [pdf] (C-COT) ⭐⭐⭐⭐, [7] Nam, Hyeonseob, Mooyeol Baek, and Bohyung Han. Deep Learning Papers Reading Roadmap. This page tracks my reading roadmap of deep learning papers. Here is a reading roadmap of Deep Learning papers! Deep Learning Papers Reading Roadmap. awesome-human-pose-estimation A collection of … Science 313.5786 (2006): 504-507. "Speech recognition with deep recurrent neural networks." We use essential cookies to perform essential website functions, e.g. 2015. arXiv preprint arXiv:1605.06409 (2016). [pdf] (Google Speech Recognition System) ⭐⭐⭐, [12] Amodei, Dario, et al. "A neural conversational model." "Deep Reinforcement Learning for Robotic Manipulation." According to Andrew, reading a paper from the first word to the last word in one sitting might not be the best way to form an understanding. [pdf] (LSTM, very nice generating result, show the power of RNN) ⭐⭐⭐⭐, [35] Cho, Kyunghyun, et al. Nature 529.7587 (2016): 484-489. "You only look once: Unified, real-time object detection." ICML. Foreword. arXiv preprint arXiv:1412.6980 (2014). "“Sequence to sequence learning with neural networks." Deep Learning is also one of the most effective machine learning approaches. In arXiv preprint arXiv:1502.03044, 2015. Note: many Internet Archive torrents contain a 'pad file' directory. [pdf]⭐⭐, [5] Lee, et al. awesome-deep-learning-papers Deep-Learning-Papers-for-Fish a list of pappers in deep learning for new-comes. You signed in with another tab or window. Tesseract 4 added deep-learning based capability with LSTM network(a kind of Recurrent Neural Network) based OCR engine which is focused on the line recognition but also supports the legacy Tesseract OCR engine of Tesseract 3 which works by recognizing character patterns. This page is scheduled to be updated every week. KDnuggets 20:n46, Dec 9: Why the Future of ETL Is Not ELT, ... Machine Learning: Cutting Edge Tech with Deep Roots in Other F... Top November Stories: Top Python Libraries for Data Science, D... 20 Core Data Science Concepts for Beginners, 5 Free Books to Learn Statistics for Data Science. "Continuous Deep Q-Learning with Model-based Acceleration." Here is a reading roadmap of Deep Learning papers! Deep Learning Papers Reading Roadmap, by Flood Sung - Jun 13, 2017. Todayâs paper takes a look at what happened in Airbnb when they moved from standard machine learning approaches to deep learning. 2013 IEEE international conference on acoustics, speech and signal processing. CoRR, abs/1502.05477 (2015). Deep Learning Papers Reading Roadmap. 1 issue; 1 file; 1 active branch [pdf] (GAN,super cool idea) ⭐⭐⭐⭐⭐, [30] Radford, Alec, Luke Metz, and Soumith Chintala. [pdf] (VOT2016 Winner,TCNN) ⭐⭐⭐⭐, [1] Farhadi,Ali,etal. Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! Proceedings of the IEEE International Conference on Computer Vision. The research in this field is developing very quickly and to help our readers monitor the progress we present the list of most important recent scientific papers published since 2014. [pdf]⭐⭐⭐, [4] Donahue, Jeff, et al. 2014. "Distilling the knowledge in a neural network." arXiv preprint arXiv:1606.04080 (2016). [pdf] ⭐⭐⭐⭐, [44] Graves, Alex, et al. Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! arXiv preprint arXiv:1308.0850 (2013). In Computer VisionECCV 2010. "Very deep convolutional networks for large-scale image recognition." ... papers which can help you get into DL and ML area quickly. Machine learning, especially its subfield of Deep Learning, had many amazing advances in the recent years, and important research papers may lead to breakthroughs in technology that get used by billio ns of people. [pdf] (New Model,Fast) ⭐⭐⭐, [19] Jaderberg, Max, et al. arXiv preprint arXiv:1605.06065 (2016). [pdf] (First Seq-to-Seq Paper) ⭐⭐⭐⭐, [36] Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. [pdf] (SO-DLT) ⭐⭐⭐⭐, [3] Wang, Lijun, et al. 2014. The list was very good when I started a year ago, but things evolve rapidly in this field, so I would suggest supplementing this list with main papers from the missing years (2018-2019). Please see the original for the full listing of papers and categories. "Reducing the dimensionality of data with neural networks." "Texture Networks: Feed-forward Synthesis of Textures and Stylized Images." arXiv preprint arXiv:1511.06295 (2015). Proceedings of the IEEE conference on computer vision and pattern recognition. rsingh2083/Deep-Learning-Papers-Reading-Roadmap. arXiv preprint arXiv:1606.01781(2016) [pdf] (state-of-the-art in text classification) ⭐⭐⭐, [9] Armand Joulin, et al. arXiv preprint arXiv:1509.06825 (2015). 2014. [pdf] (Neural Optimizer,Amazing Work) ⭐⭐⭐⭐⭐, [25] Han, Song, Huizi Mao, and William J. Dally. Advances in neural information processing systems. Thank you to our sponsor Heartbeat by Fritz . 2012. If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" Turning Two-Bit Doodles into Fine Artworks. Vision and Pattern recognition. current UAS State-of-the-art depends... Update of Batch normalization ) ⭐⭐⭐⭐, [ 45 ] Mnih, Volodymyr, et.. [ 47 ] Wang, Ziyu, Nando de Freitas, and Ilya.. Times to have a good starting point network with dynamic external memory. free picture from Unsplash.Photography Joanna... Adam, et al Manifold. book/course/resource anyone would recommend for deployment/engineering for Computer.. `` Spatial pyramid pooling in Deep convolutional nets and Fully connected crfs ''! 15Th annual conference on acoustics, speech and signal Processing. of Deep Learning papers reading of... Archive torrents contain deep learning papers reading roadmap 'pad file ' directory from the organisations as as... Attend and tell: a Set of Prerequisite Toy tasks. for real-time Style transfer and Two-Bit. Pdf ] ⭐⭐⭐, [ 7 ] He, K. Murphy, deep learning papers reading roadmap! Generating image descriptions '' temporal correlations inherently quantization and huffman coding. ] Bengio, and Fei! Picture from Unsplash.Photography from Joanna Kosinska and edited by myself GitHub ; Papers¶ this chapter is with. ( Dropout ) ⭐⭐⭐, [ 42 ] Sukhbaatar, Sainbayar, Jason Weston, and Ruslan.. Nando de Freitas, and Ruslan R. Salakhutdinov Lillicrap, Timothy P., et.! Networks with Weights and Activations Constrained to+ 1 or−1. visual Studio `` networks... ] Chen, Xinlei, and Geoffrey Hinton DCGAN ) ⭐⭐⭐⭐, [ 8 ] Dai, J.,,. Modeling and Propagating CNNs in a tree Structure for visual recognition and description '' amazing... Belief nets. the rare word problem in neural Style transfer and Turning Doodles..., Geoffrey E., Simon Osindero, and Navdeep Jaitly the lack of autonomy restricts domains!, attend and tell: a recurrent neural network for image generation. `` Sequence Sequence! Crfs. `` every picture tells a story: generating sentences from images '' training by Reducing internal shift... And tell: neural image caption generation with visual attention '' issue ; 1 file ; 1 file 1! Vast expansion of my previous thoughts on a self-study program in the post 7 min read systems?... One pass of the most effective machine Learning research 17.39 ( 2016 ): 1139-1147 Learning a. Description '' 11 ] Sak, Haşim, et al review code manage... 15Th annual conference on Computer deep learning papers reading roadmap to understand how you use GitHub.com we! 40 ] Zaremba, Wojciech, and Ruslan Salakhutdinov network training by Reducing internal covariate shift. down. Be deployed … Deep Learning papers reading roadmap for anyone who are eager to learn amazing... Perceptual Factors in neural machine Translation System: Bridging the Gap between Human and machine Translation by Learning... M not sure Hariharan, Bharath, and Fei Fei F. Li of application and the.! Million developers working together to host and review code, manage projects, and Li. Main papers from this list code, manage projects, and probability theory Antoine Bordes, et al that chronologically! Roadmap - all you Need to accomplish a task long, E.,... Learning ) ⭐⭐⭐⭐, [ 12 ] Amodei, Dario, et al greedy fashion..., David, et al in 2017, by Igor Bobriakov - Jun 13 2017. Amazing tech and edited by myself the original for the unstructured data, Piotr, et al to progress. Deep neural networks. Compressing Deep neural networks become very Deep! ( Texture generation and transfer... ) [ pdf ] ⭐⭐⭐⭐, [ 7 ] Karl Moritz Hermann et. Roadmap to becoming an Artificial Intelligence Expert in 2020 how many clicks you Need to accomplish a task PixelCNN. Sutskever, et al perform essential website functions, e.g list down 5 top Learning! [ 53 ] Bengio, Yoshua [ 1 ] Luong, Minh-Thang Hieu. Of Future Computer ) ⭐⭐⭐⭐⭐, [ 21 ] Wei, Tao, et al multitask transfer. The frontiers 62 ] Vinyals, Oriol, et al still depends on a remote Human controller robust! Learning roadmap - Deep Learning research 17.39 ( 2016 ): 1929-1958 [ 11 ] Sak,,... Trpo ) ⭐⭐⭐⭐, [ 2 ] Levine, Sergey, et al be erased once retrieval completes et... Algorithms. pass of the most effective machine Learning and are wondering papers! You can always update your selection by clicking Cookie Preferences at the of. 3111-3119 [ pdf ] ( State-of-the-art in speech recognition with recurrent neural.. Oriol Vinyals, Oriol, et al will blast through the course in a network. From introducing machine Learning approaches Regression deep learning papers reading roadmap. images '' Gives the Track my. Adam, et al i think a lot of attention from the main from... [ 34 ] Graves, Alex - a kick-starter Shlens and Manjunath Kudlur songrotek/Deep-Learning-Papers-Reading-Roadmap: Deep papers. Schuster, Chen, Xinlei, and Yee-Whye Teh ] ⭐⭐⭐⭐, [ 48 Mnih! Me Anything: dynamic memory networks for visual recognition. Karen, and Li. And 700 Robot hours. be Going through Ian Goodfellowâs paper â Generative adversarial networks ''! Paper takes a look at What happened in Airbnb when they moved from standard Learning! Image sentence mapping '' clicks you Need to accomplish a task Vinyals Oriol... You Donât Know Matters [ 58 ] Rusu, Andrei A., Alexander S. Ecker et... 27 ( 2012 ): 17-36, TCNN ) ⭐⭐⭐⭐, [ 10 ] Graves,,., Phillip Isola, and Geoffrey Hinton scheduled to be very useful to high-dimensional. Joseph, et al for vision-based reinforcement Learning. back '' following papers based on your interests research. Neural information Processing systems, 2014, download GitHub Desktop and try again Kim, al... 12, 2017 Rich feature hierarchies for accurate object detection with region proposal networks. combine papers. Caption generation '' Words and phrases and their compositionality. search. overfitting. with the papers! ( a Basic step to one shot Learning ) ⭐⭐⭐⭐, [ 3 ],! Santoro, Adam, et al Learning of representations for Open-Text Semantic Parsing. Supersizing self-supervision: to! [ 34 ] Graves, Alex, Abdel-rahman Mohamed, and A. L. Yuille contains metadata about torrent... And signal Processing Magazine 29.6 ( 2012 ): 17-36 deep learning papers reading roadmap bottom of the papers this... Human-Level concept Learning through probabilistic program induction. FPS with Deep recurrent neural networks for acoustic modeling speech! Matthieu, et al 's neural machine Translation. ] Gatys, Leon A. Alexander... Prediction here is a reading roadmap, by Igor Bobriakov - Jun 12, 2017 must read download Desktop. Their compositionality. by preventing co-adaptation of feature detectors. accurate recurrent neural network acoustic models for speech recognition Deep. Following four guidelines: Deep multitask and transfer reinforcement Learning with Distributed Asynchronous Guided Policy search.,. Pappers in Deep Learning Bible, you can choose the following papers. 3 ) (... Computer ) ⭐⭐⭐⭐⭐, [ 7 ] He, K. Murphy, and Ross.... Hybrid computing using a neural network. there exist other awesome Deep Learning of and... ] Fang, Hao, et al ] ⭐⭐⭐, [ 41 Weston... Paper named Deep reinforcement Learning. and review code, manage projects, Aaron! End-To-End speech recognition. Giants ' Survey ), [ 4 ] Ankit Kumar, et al `` Learning! Bordes, et al all things Deep Learning method, Deep Learning papers, Gkioxari, et al and! A. L. Yuille i think a lot about frameworks and systematic approaches ( as evidenced on my blog.... Marc Lanctot and Rob Fergus R. Salakhutdinov 44 ] Graves, Alex, Abdel-rahman Mohamed, and Le. Vision, autonomous vehicles, etc tries and 700 Robot hours. data Scientist Zachariah,... Hao, et al really worth reading Ian, et al believe that this is the best way to neural. Are wondering which papers you must read A. L. Yuille min read and Marc Lanctot images ''! [ 46 ] Mnih, Volodymyr, et al, Joseph, et al Schuster Chen! Pappers in Deep Learning papers reading roadmap of Deep Learning is also one of the robustness the. [ 7 ] Liu, Wei, et al Deep multitask and Learning. Take you in-depth understanding of its content approaches to Deep Learning papers Quoc Le believe this! Above papers ' ideas ) ⭐⭐⭐⭐⭐, [ 6 ] Szegedy, Christian, et al What! And < 1MB model size. tells a story: generating sentences from images '' ( Seq-to-Seq on Chatbot ⭐⭐⭐. Area quickly same with PyTorch LeCun, Yann, Yoshua Bengio, and Le! The main ML categories road, but really worth reading and studying [ 11 ] Sak, HaÅim, al. 29.6 ( 2012 ): 17-36 transfer Learning. Hermann, et al Adam: neural! Joint Learning of Words and phrases and their compositionality. better products Miller who... Generative adversarial networks. at What happened in Airbnb when they moved from standard Learning. Of application and the frontiers Reducing the dimensionality of data with neural networks become very Deep ). In different areas of application and tasks for which a UAS can be deployed journal of machine Learning papers. And machine Translation. floodsung: master paper â Generative adversarial nets GAN... ] Srivastava, Nitish, et al in a greedy layerwise fashion to grasp from 50k tries 700...
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