Topic 7: Neural Networks and Deep Learning 3358


Title (link) Author Date Votes Error
Kings, Queens, and Counts Tom McCoy 2016
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Nothing but Net(works) Tom McCoy 2017
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Part 1 - Artificial Neural Networks Author Unknown 2017
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Beyond Seq2Seq with Augmented RNNs Edward Grefenstette 2016
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Deep Learning Book Part 2 Alena Kruchkova 2017
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Million Song Dataset Challenge Author Unknown 2011
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Natural Language Processing with Representation Learning Samuel Bowman and Kyunghyun Cho 2017
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Applications of Deep Neural Networks Jeff Heaton 2018
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Analyzing the Meaning of Sentences Steven Bird, Ewan Klein, Edward Loper 2014
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Neural Networks and Deep Learning (Course 1 of the Deep Learning Specialization) Author Unknown 2017
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PyTorch Lecture 01: Overview Sung Kim 2017
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Tensorflow for Deep Learning Research - Lecture 4 Labhesh Patel 2017
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Understanding Long Short-Term Memory Networks (LSTMs) rubikscode 2018
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Applied Deep Learning - Part 1: Artificial Neural Networks Arden Dertat 2017
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Mini-Course on Long Short-Term Memory Recurrent Neural Networks with Keras Jason Brownlee 2017
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Deep Learning Book Part 1 Alena Kruchkova 2017
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Introduction to TensorFlow Chris Manning, Richard Socher 2017
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Network Science Albert-Laszlo Barabasi 2015
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Introduction to Recurrent Neural Networks rubikscode 2018
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But what *is* a Neural Network | Deep learning, Part 1 3Blue1Brown 2017
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CMU Neural Nets for NLP 2017 Graham Neubig 2017
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Artificial Neural Networks with Python - 5 - Single Layer Neural Net Cristi Vlad 2017
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Tensorflow for Deep Learning Research - Lecture 3 Labhesh Patel 2017
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Introduction to Convolutional Neural Networks rubikscode 2018
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Tensorflow for Deep Learning Research - Lecture 5_2 Labhesh Patel 2017
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Neural Networks for Machine Learning Geoffrey Hinton 2016
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NIPS 2016 Spotlight Videos NIPS Conference 2016
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Deeplearning.ai Author Unknown 2017
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Stanford Tensorflow Tutorials Huyen Nguyen 2017
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Introduction to TensorFlow – With Python Example rubikscode 2018
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Part 2 - Case Studies Author Unknown 2017
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Deeplearning.ai Author Unknown 2017
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Alena Kruchkova Youtube Channel Alena Kruchkova 2017
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Two Ways to Implement LSTM Network using Python – with TensorFlow and Keras rubikscode 2018
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Tensorflow for Deep Learning Research - Lecture 2 Labhesh Patel 2017
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DeepLearning.TV Author Unknown 2015
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TensorFlow and Deep Learning without a PhD Martin Gorner 2017
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Artificial Neural Networks with Python - 1 - Introduction Cristi Vlad 2017
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Structuring Machine Learning Projects (Course 3 of the Deep Learning Specialization) Author Unknown 2017
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Deepschool.io Sachinthaka R. Abeywardana 2017
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Common Neural Network Activation Functions rubikscode 2017
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Applied Deep Learning - Part 2: Real World Case Studies Arden Dertat 2017
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Information Theory of Deep Learning Naftali Tishby 2017
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CMU Neural Nets for NLP 2017(9): Attention Graham Neubig 2017
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CS224N Midterm Review Nishith Khandwala, Barak Oshri, Lisa Wang, Juhi Naik 2017
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Tensorflow for Deep Learning Research - Lecture 1 Labhesh Patel 2017
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Intro to ML Lecture Notes NYU DL 2018
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Deep Learning: Theory, Algorithms, and Applications Author Unknown 2017
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Improving Deep Neural Networks: Hyperparameter Author Unknown 2017
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A Step by Step Introduction to Deep Learning with Python: Day 1 - What is Deep Learning? Machine Learning TV 2017
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Tensorflow for Deep Learning Research - Lecture 5_1 Labhesh Patel 2017
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Implementation of Convolutional Neural Network using Python and Keras rubikscode 2018
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Title (link) Author Date Votes Error
The Multi-Genre NLI Corpus Adina Williams, Nikita Nangia, Angeliki Lazaridou, Sam Bowman 2017
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Word Vectors Manaal Faruqui, Chris Dyer 2016
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Course Project Reports for 2015 for CS224n: Natural Language Processing with Deep Learning Richard Socher (Instructor) 2015
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The 6th Open Challenge on Question Answering Over Linked Data Christina Unger 2016
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Pubmed Dataset George Brokos, Ion Adroutsopoulos 2018
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Pre-trained word vectors Piotr Bojanowski, Edouard Grave, Arm, Joulin, Tomas Mikolov 2016
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Course Project Reports for 2016 for CS224n: Natural Language Processing with Deep Learning Stanford CS224n 2016
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WikiTableQuestions: a Complex Real-World Question Understanding Dataset Ice Pasupat 2016
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The Quick, Draw! Dataset Google Creative Lab 2017
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Downsampled ImageNet Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu 2016
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Course Project Reports for 2017 for CS224n: Natural Language Processing with Deep Learning Stanford CS224n 2017
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A Reading Comprehension Dataset for the Artificial Intelligence research community Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder and Li Deng 2017
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A New Multi-Turn Multi-Domain Task-Oriented Dialogue Dataset Stanford 2017
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Automatic Generation of Story Highlights Data Set Kristian Woodsend, Mirella Lapata 2010
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Maluuba NewsQA Dataset Maluuba 2017
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Addressee and Response Selection Task Hiroki Ouchi, Yuta Tsuboi 2016
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English word vectors FaceBook fastText team 2017
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Title (link) Lecturer Date Votes Error
Gradients as Dual Vectors David McAllester 2017
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Feedforward neural network - capacity of single neuron Hugo Larochelle 2017
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Generative Adversarial Networks François Fleuret 2019
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Neural Machine Translation Richard Socher 2016
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Feedforward neural network - artificial neural network Hugo Larochelle 2017
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Neural Networks: Part 1 Hugo Larochelle 2018
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Deep Learning Ruihong Huang 2017
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Long Short Term Memory Networks Dragomir Radev 2017
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CS11-747 Neural Networks for NLP Convolutional Networks Graham Neubig 2017
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Sentence Representations Stephen Clark 2017
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Text generation Yangfeng Ji 2018
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Image Classification Roger Grosse 2018
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Neural Networks Ralph Grishman 2018
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How to Use Tensorboard (LIVE) Siraj Raval 2017
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Examples of Viterbi, Forward, and Backward Jacob Eisenstein 2014
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Deep Learning David R. Mortensen, Alan W. Black 2018
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Introduction to TensorFlow Richard Socher 2018
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EM and PCA Matt Gormley 2016
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Exotic Deep Learning Efstratios Gavves 2018
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Case Studies Kian Katanforoosh 2018
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Deep learning - deep belief network Hugo Larochelle 2017
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Bias-variance dilemma François Fleuret 2019
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TensorFlow Tutorial Richard Socher 2016
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Training neural networks - parameter gradient Hugo Larochelle 2017
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Computation graphs Jonathan Berant 2017
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Neural Question Answering Dragomir Radev 2018
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Deep learning - difculty of training Hugo Larochelle 2017
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L2 and L1 penalties François Fleuret 2019
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Feedforward Neural Networks Michael Collins, 2018
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Autoencoder - denoising autoencoder Hugo Larochelle 2017
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CS11-747 Neural Networks for NLP Attention Graham Neubig 2017
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Representing words Sida Wang 2018
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Recurrent Neural Networks Yoav Artzi 2018
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Applications III: Dialogue Greg Durrett 2018
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Neural Networks Xavier Bresso 2017
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Introduction To Deep Learning Alexander Amini 2018
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Deep Learning & Neural Networks Nathan Schneider 2018
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Sparse coding - ZCA preprocessing Hugo Larochelle 2017
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A Beginner's Guide to the Mathematics of Neural Networks A.C.C. Coolen 1998
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Conditional GANs Svetlana Lazebnik 2018
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Introduction to Neural Networks and Deep Learning Dragomir Radev 2017
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Lecture 7: Sequence-to-Sequence Modeling and Attention Kevin Gimpel 2017
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Long Short Term Memory Stephen Clark 2017
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Face recognition Kian Katanforoosh 2018
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ResNets and Attention Roger Grosse 2018
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Recurrent Neural Networks Dragomir Radev 2018
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Autoencoder - definition Hugo Larochelle 2017
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DataLoader and neuro-surgery François Fleuret 2019
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Understanding How ConvNets Works Roger Grosse 2018
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Computation Graphs and Backpropagation David McAllester 2017
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Sequence to sequence models Kian Katanforoosh 2018
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Computer vision - discrete convolution Hugo Larochelle 2017
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Recurrent Neural Networks François Fleuret 2019
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Wrap up: LSTMs and Recursive Neural Networks Richard Socher 2016
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Deep learning - unsupervised pre-training Hugo Larochelle 2017
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Neural Network Methods for Natural Language Processing Yoav Goldberg 2017
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Machine Translation Julia Hockenmaier 2018
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Neural Machine Translation Dragomir Radev 2017
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Neural Tips and Tricks Recurrent Neural Networks Richard Socher 2016
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Word Embeddings Marine Carpuat 2018
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Introduction to NLP and Deep Learning Richard Socher 2018
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Sparse coding - dictionary update with projected gradient descent Hugo Larochelle 2017
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Pooling François Fleuret 2019
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Representation of Stationary Process Joan Bruna 2016
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Training neural networks - regularization Hugo Larochelle 2017
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Feedforward Neural Networks for NLP Stephen Clark 2017
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Basic model structures Sida Wang 2018
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Natural Language Processing Machine Translation Dan Klein 2014
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Neural Nets IV: CNNs, Neural CRFs Greg Durrett 2018
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Transformer Networks and CNNs Richard Socher 2018
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Neural Networks Dan Roth 2018
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Recurrent Neural Networks Efstratios Gavves 2018
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Tensor basics and linear regression François Fleuret 2019
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Deep Neural Networks Kian Katanforoosh 2018
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Neural networks David Sontag 2016
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Neural Machine Translation Dragomir Radev 2018
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Sparse coding Hugo Larochelle 2017
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Rectifiers François Fleuret 2019
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Neural Networks in Structured Prediction 2 Chris Dyer 2015
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Natural language processing - multitask learning Hugo Larochelle 2017
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DISTRIBUTIONAL SEMANTICS Trevor Cohn 2018
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Convolutional networks Svetlana Lazebnik 2018
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Lecture 2: Elements of Neural NLP Kevin Gimpel 2017
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Natural language processing - tree inference Hugo Larochelle 2017
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Non-volume preserving networks François Fleuret 2019
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Neural Networks in Speech Recognition Richard Socher 2016
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Training CRFs - pseudo likelihood Hugo Larochelle 2017
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Deep learning in the brain Blake Aaron Richards 2018
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Distributional Semantics Ruihong Huang 2017
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Recurrent Neural Networks Dragomir Radev 2017
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Lecture 3: Words Kevin Gimpel 2016
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Sentence Representations Stephen Clark 2017
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Sequence-to-sequence models and attention mechanism Yangfeng Ji 2018
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Autoencoders Roger Grosse 2018
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Deep Graphical Models II David McAllester 2017
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Deep Reinforcement Learning Pieter Abbeel 2017
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Examples of Viterbi, Forward, and Backward Jacob Eisenstein 2014
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Multilingual Models and Open Research Questions Marine Carpuat 2018
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Backpropagation and Project Advice Richard Socher 2018
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Neural Networks and Backpropagation Matt Gormley 2016
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Memory Networks for Language Understanding Efstratios Gavves 2018
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Attacking Networks with Adversarial Examples Kian Katanforoosh 2018
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Restricted Boltzmann machine - contrastive divergence (parameter update) Hugo Larochelle 2017
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Tensor internals François Fleuret 2019
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Dynamic Memory Networks for Question Answering over Text and Images Richard Socher 2016
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Autoencoders Hugo Larochelle 2017
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Word embeddings Jonathan Berant 2017
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Bag-of-Words Methods for Text Mining Ralph Grishman 2018
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Long Short Term Memory Networks Dragomir Radev 2018
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Natural language processing - convolutional network Hugo Larochelle 2017
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PyTorch optimizers François Fleuret 2019
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Recurrent Networks, and Attention for Statistical Machine Translation Michael Collins, 2018
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Convolutional Neural Networks for Computer Vision Efstratios Gavves 2018
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CS11-747 Neural Networks for NLP Why is word2vec so fast? Efciency tricks for neural nets Graham Neubig 2017
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Word Embeddings Sida Wang 2018
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Lexical Semantics Tom Kwiatkowski 2016
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Applications II: Summarization Greg Durrett 2018
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Gradient Descent Tricks Xavier Bresso 2017
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Faster ML Development with TensorFlow Alexander Amini, Shanqing Cai 2018
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Autoencoder - example Hugo Larochelle 2017
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Introduction to Deep Learning Alexander Amini 2018
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Generative adversarial networks Svetlana Lazebnik 2018
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Lecture 3: Word Embeddings Kevin Gimpel 2017
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Tensorflow Stephen Clark 2017
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Object Detection Kian Katanforoosh 2018
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Recurrent Neural Networks Roger Grosse 2018
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Introduction to Neural Networks and Deep Learning Dragomir Radev 2018
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Feedforward neural network - activation function Hugo Larochelle 2017
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Using GPUs François Fleuret 2019
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LSTM David Bamman 2017
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Rate-Distortion Autoencoders David McAllester 2017
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NLP and Word Embeddings Kian Katanforoosh 2018
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Feedforward neural network - biological inspiration Hugo Larochelle 2017
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Model persistence and checkpoints François Fleuret 2019
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Recurrent Neural Networks Richard Socher 2016
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Restricted Boltzmann machine - contrastive divergence Hugo Larochelle 2017
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Intro to Deep Learning Tess Fernandez 2018
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Feed-forward neural networks and back propagation algorithm Yangfeng Ji 2018
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Neural Parsing Dragomir Radev 2017
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CS11-747 Neural Networks for NLP Multi-task, Multi-lingual Graham Neubig 2017
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Feedforward Neural Language Models Marine Carpuat 2018
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Generative adversarial networks Yangfeng Ji 2018
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Implementing autograd Roger Grosse 2018
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Convolutions François Fleuret 2019
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Embeddings, Extensions to Non-Euclidean Domains, Representations of Stationary Processes Joan Bruna 2016
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Feedforward neural network - multilayer neural network Hugo Larochelle 2017
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Introduction to Neural Networks for NLP Stephen Clark 2017
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AutoML: Automated Machine Learning Sergey Levine 2018
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Natural Language Processing Machine Translation Dan Klein 2014
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Neural Nets III: RNN encoders Greg Durrett 2018
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Advanced Attention Richard Socher 2018
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EM Algorithm Dan Roth 2018
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Understanding Convnets and Knowledge Transfer Efstratios Gavves 2018
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Neural Nets (wrap-up) and Decision Trees Pieter Abbeel, Dan Klein 2018
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language model Hugo Larochelle 2017
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One hidden layer Neural Network Kian Katanforoosh 2018
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Deep Learning II Furong Huang 2018
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Neural Summarization Dragomir Radev 2018
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Sparse coding - online dictionary learning algorithm Hugo Larochelle 2017
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Benefits of depth François Fleuret 2019
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Deep Learning Yejin Choi 2018
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Sparse coding - dictionary learning algorithm Hugo Larochelle 2017
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A SUBJECT OVERVIEW Trevor Cohn 2018
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Multi-layer networks, backpropagation Svetlana Lazebnik 2018
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Lecture 5: Sequence-to-Sequence Modeling and Sentence Embeddings Kevin Gimpel 2017
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What is really happening? François Fleuret 2019
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Feed-forward neural network - capacity of neural network Hugo Larochelle 2017
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Denoising and variational autoencoders François Fleuret 2019
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Word Window Classification and Neural Networks Richard Socher 2016
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Recursive neural network Hugo Larochelle 2017
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Recurrent Nets and Attention for System 2 Processing Yoshua Bengio 2018
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Sequence Models Ruihong Huang 2017
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Tools for Deep Learning Dragomir Radev 2017
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Lecture 5: Word Vectors Kevin Gimpel 2016
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Convolutional Neural Networks Stephen Clark 2017
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Recurrent neural network language modeling Yangfeng Ji 2018
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Convolutional Networks Roger Grosse 2018
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Variational Autoencoders David McAllester 2017
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Sequence to Sequence Models for Machine Translation Marine Carpuat 2017
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Attention Models Marine Carpuat 2018
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Neural Networks Richard Socher 2018
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PCA and Neural Networks Matt Gormley 2016
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Deep Graphical Models I David McAllester 2017
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The mathematics of deep learning Kian Katanforoosh 2018
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Restricted Boltzmann machine - inference Hugo Larochelle 2017
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Neural Networks for NLP Julia Hockenmaier 2018
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Convolutional Neural Networks (for NLP) Richard Socher 2016
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Deep learning - dropout Hugo Larochelle 2017
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The Expectation-Maximization Algorithm Eric Xing 2014
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Seq2Seq, Attention; Generation and Dialog Julia Hockenmaier 2018
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Neural Generation, Dialogue Systems Dragomir Radev 2017
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Tools for Deep Learning Dragomir Radev 2018
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Deep learning - DBN pretraining Hugo Larochelle 2017
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Stochastic gradient descent François Fleuret 2019
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Word Embeddings in Feedforward Networks, Tagging and Dependency Parsing using Feedforward Networks Michael Collins, 2018
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Introduction to Neural Networks and Deep Learning Efstratios Gavves 2018
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CS11-747 Neural Networks for NLP Debugging Neural Networks for NLP Graham Neubig 2017
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seq2seq and attention Sida Wang 2018
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Statistical NLP Tom Kwiatkowski 2016
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Applications I: Reading comprehension / MemNets Greg Durrett 2018
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Future of NLP Models, Multi-task Learning and QA Systems Richard Socher 2018
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Sparse coding - inference (ISTA algorithm) Hugo Larochelle 2017
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Lecture 1: Introduction Kevin Gimpel 2017
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Recurrent Neural Networks Stephen Clark 2017
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Case Studies Kian Katanforoosh 2018
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Backpropagation Roger Grosse 2018
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Neural Parsing Dragomir Radev 2018
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Restricted Boltzmann machine - extensions Hugo Larochelle 2017
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Residual networks François Fleuret 2019
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stocastic gradient descent Jinho D. Choi 2017
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Computer vision - convolutional network Hugo Larochelle 2017
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Constructing and Evaluating Word Embeddings Marek Rei, Ekaterina Kochmar 2016
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Adversarial examples Svetlana Lazebnik 2018
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Introduction and Historical Notes David McAllester 2017
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Recurrent Neural Networks Kian Katanforoosh 2018
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Feedforward neural network Hugo Larochelle 2017
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Conditional GAN and image translation François Fleuret 2019
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Word Vectors Richard Socher 2016
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Restricted Boltzmann machine - free energy Hugo Larochelle 2017
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Introduction to Convolutional Neural Networks Jon Shlens 2018
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Text classification, bag-of-words representations Yangfeng Ji 2018
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Convolutional Neural Networks Dragomir Radev 2017
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CS11-747 Neural Networks for NLP Models of Words Graham Neubig 2017
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Neural Networks: Computation Graphs, Backpropagation Marine Carpuat 2018
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Representation learning on texts Yangfeng Ji 2018
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Neural Networks for Machine Learning Roger Grosse 2018
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CNN and near-diagonalisation Joan Bruna 2016
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Training neural networks Hugo Larochelle 2017
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LSTM GRU Jonathan Berant 2017
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TensorFlow and Neural Nets Review Session (notebook) Sergey Levine 2018
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Natural Language Processing: Machine Translation III Dan Klein 2014
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Neural Nets II: Word embeddings Greg Durrett 2018
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Vanishing Gradients, Fancy RNNs Richard Socher 2018
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Neural Networks, Backpropagation, Recurrent Networks, Convolutional Networks, Deep Belief Networks, Deep Boltzman Machines Maria-Florina Balcan 2015
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Unsupervised, Generative & Adversarial Networks Efstratios Gavves 2018
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DL for Healthcare Kian Katanforoosh 2018
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Deep learning Hugo Larochelle 2017
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PyTorch modules and batch processing François Fleuret 2019
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Neural Networks I Furong Huang 2018
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Neural Architectures, Training Neural Networks Dragomir Radev 2018
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Natural language processing - hierarchical output layer Hugo Larochelle 2017
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Architecture choice and training protocol François Fleuret 2019
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Recurrent Networks, and LSTMs, for NLP Michael Collins, 2018
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Training neural networks - activation function derivative Hugo Larochelle 2017
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Vector Semantics Dan Jurafsky 2017
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Bias-variance tradeoff, validation Svetlana Lazebnik 2018
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Lecture 8: Neural Machine TranslaEon Kevin Gimpel 2017
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Current applications and success François Fleuret 2019
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Basics of Neural Network Programming Kian Katanforoosh 2018
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Deep learning - motivation Hugo Larochelle 2017
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Autoencoders François Fleuret 2019
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Sequence to Sequence Learning Richard Socher 2016
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Word representations Hugo Larochelle 2017
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Toward Theoretical Understanding of Deep Learning Sanjeev Arora 2018
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Sequence-to-sequence models with attention Svetlana Lazebnik 2018
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Word Embeddings Dragomir Radev 2017
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Lecture 11: Recurrent and Convolutional Neural Networks in NLP Kevin Gimpel 2016
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Better Conditional Language Modeling Stephen Clark 2017
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Word embeddings (II): Evaluation and problems Yangfeng Ji 2018
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Boltzmann Machines Roger Grosse 2018
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Deep Learning Percy Liang 2017
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Encoder-decoder models, beam search Marine Carpuat 2018
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Word Vectors 2 Richard Socher 2018
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CNNs Matt Gormley 2016
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Deep Reinforcement Learning David McAllester 2017
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Deep Learning Intuition Kian Katanforoosh 2018
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Training neural networks - loss function Hugo Larochelle 2017
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Word embeddings and translation François Fleuret 2019
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AWS Tutorial Richard Socher 2016
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Training neural networks - empirical risk minimization Hugo Larochelle 2017
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Dive into Deep Learning MXNet Community 2018
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Word Embeddings and Recurrent Nets Julia Hockenmaier 2018
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Neural Question Answering Dragomir Radev 2017
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Sequence to Sequence Models for Machine Translation 2 Marine Carpuat 2017
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Natural language processing - recursive network Hugo Larochelle 2017
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Cross-entropy loss François Fleuret 2019
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Distributed representations Christopher Manning 2017
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Sparse coding - definition Hugo Larochelle 2017
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CS11-747 Neural Networks for NLP Models of Dialog and Graham Neubig 2017
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RNN cell structures Sida Wang 2018
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Morphological analysis Tom Kwiatkowski 2016
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Machine Translation II: Neural Greg Durrett 2018
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Advanced Architectures and Memory Networks Richard Socher 2018
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Autoencoder - contractive autoencoder Hugo Larochelle 2017
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Structured Prediction with ConvNets Efstratios Gavves 2018
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Lecture 4: Word Embeddings (2) Kevin Gimpel 2017
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Word Embeddings Stephen Clark 2017
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Convolutional Neural Networks Kian Katanforoosh 2018
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Neural Style Roger Grosse 2018
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Neural Generation, Dialogue Systems Dragomir Radev 2018
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Deep learning - example Hugo Larochelle 2017
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Batch normalization François Fleuret 2019
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Report
Character-level text classification puyash 2017
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BioPy David Cunningham, Jared M. Smith 2015
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Machine Learning with TensorFlow: code Nishant Shukla 2017
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TensorLy: Tensor Learning in Python Jean Kossaifi, Yannis Panagakis and Maja Pantic 2018
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Latent Alignment and Variational Attention harvardnlp 2018
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Unsupervised Text Segmentation Liang Wang 2016
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NeuroNER Franck Dernoncourt, Ji Young Lee, Ozlem Uzuner, Peter Szolovits 2016
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learn2sum Chris Kedzie 2016
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word2vec-recommender Manas Ranjan Kar, Akhil Gupta 2017
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Text_Summarization_with_Tensorflow thomasschmied 2018
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Question Answering Neural Network with Trans-Sentential Averaging John Co-Reyes 2014
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Structured Inference Networks for Nonlinear State Space Models Rahul G. Krishnan, Uri Shalit, David Sontag 2017
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ZhuSuan Author Unknown 2017
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Transformer Samuel Lynn-Evans 2018
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TellinaTool/awesome_nmt Tellina 2017
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Practical Machine Learning with Python dipanjanS 2018
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Pyevolve Christian S. Perone 2009
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Tensorflow tutorial on convolutional neural networks Cole Murray 2017
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TensorBoard for PyTorch Tzu-Wei Huang 2018
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Potara: Multi-document summarization tool sildar 2015
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Seq2seq Chatbot for Keras Oswaldo Ludwig 2017
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Mindpark Danijar Hafner 2017
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TextKBQA Rajarshi Das, Manzil Zaheer, Siva Reddy, Andrew McCallum 2017
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word2viz Julia Bazi?ska and Piotr Migda? 2018
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ResearchCyc Author Unknown 2018
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Word2Vec Tomas Mikolov, Quoc V. Le, Ilya Sutskever 2017
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Tensorflow Implementation of Nested LSTM Cell hannw 2018
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Allen NLP The Allen Institute for Artificial Intelligence 2017
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Persontyle Workshop for Applied Deep Learning Amaia Salvador and Santiago Pascual 2017
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Incremental Word2Vec Wammar 2017
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- 0 +
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Deep Learning Indaba 2018 deep-learning-indaba 2018
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Distributed Machine Learning Toolkit Microsoft 2018
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- 0 +
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GluonNLP: Your Choice of Deep Learning for NLP dmlc 2019
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