Google Brain Team

A Learned Representation For Artistic Style

Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur

ICLR (2017)

A Neural Representation of Sketch Drawings

David Ha, Doug Eck

arXiv (2017)

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken Perlin

ICML (2017)

Acoustic Modeling for Google Home

Bo Li, Tara Sainath, Arun Narayanan, Joe Caroselli, Michiel Bacchiani, Ananya Misra, Izhak Shafran, Hasim Sak, Golan Pundak, Kean Chin, Khe Chai Sim, Ron J. Weiss, Kevin Wilson, Ehsan Variani, Chanwoo Kim, Olivier Siohan, Mitchel Weintraub, Erik McDermott, Rick Rose, Matt Shannon

INTERSPEECH 2017 (2017) (to appear)

Adversarial Attacks on Neural Network Policies

Sandy Huang, Nicolas Papernot, Ian Goodfellow, Yan Duan, Pieter Abbeel

arXiv (2017)

Adversarial Machine Learning at Scale

Alexey Kurakin, Ian J. Goodfellow, Samy Bengio

ICLR (2017)

Adversarial Training Methods for Semi-Supervised Text Classification

Takeru Miyato, Andrew M. Dai, Ian Goodfellow

ICLR (2017)

Adversarial examples in the physical world

Alexey Kurakin, Ian Goodfellow, Samy Bengio

ICLR Workshop (2017)

Bridging the Gap Between Value and Policy Based Reinforcement Learning

Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

arXiv (2017)

Bridging the Gap Between Value and Policy Based Reinforcement Learning

Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

arXiv (2017)

Capacity and Trainability in Recurrent Neural Networks

Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo

ICLR (2017)

Categorical Reparameterization with Gumbel-Softmax

Eric Jang, Shixiang Gu, Ben Poole

ICLR (2017)

Changing Model Behavior at Test-time using Reinforcement Learning

Augustus Odena, Dieterich Lawson, Chris Olah

ICLR Workshop (2017)

Cognitive Mapping and Planning for Visual Navigation

Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik

CVPR (2017)

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search

Ali Yahya, Adrian Li, Mrinal Kalakrishnan, Yevgen Chebotar, Sergey Levine

IEEE/RSJ International Conference on Intelligent Robots and Systems (2017) (to appear)

Conditional Image Synthesis With Auxiliary Classifier GANs

Augustus Odena, Christopher Olah, Jonathon Shlens

ICML (2017)

Decomposing Motion and Content for Natural Video Sequence Prediction

Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee

ICLR (2017)

Deep Information Propagation

Samuel S. Schoenholz, Justin Gilmer, Surya Ganguli, Jascha Sohl-Dickstein

ICLR (2017)

Deep Network Guided Proof Search

Sarah Loos, Geoffrey Irving, Christian Szegedy, Cezary Kaliszyk

LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning, EasyChair (2017), pp. 85-105

Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates

ShiXiang Gu, Ethan Holly, Timothy Lillicrap, Sergey Levine

ICRA (2017)

Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs

Michael Gygli, Mohammad Norouzi, Anelia Angelova

ICML (2017)

Deep Visual Foresight for Planning Robot Motion

Sergey Levine, Chelsea Finn

ICRA (2017)

Density estimation using Real NVP

Laurent Dinh, Jascha Sohl-Dickstein, Samy Bengio

ICLR (2017)

Device Placement Optimization with Reinforcement Learning

Azalia Mirhoseini, Hieu Pham, Quoc Le, Mohammad Norouzi, Samy Bengio, Benoit Steiner, Yuefeng Zhou, Naveen Kumar, Rasmus Larsen, Jeff Dean

ICML (2017)

Discrete Sequential Prediction of Continuous Actions for Deep RL

Luke Metz, Julian Ibarz, Navdeep Jaitly, James Davidson

arXiv (2017)

Explaining the Learning Dynamics of Direct Feedback Alignment

Justin Gilmer, Colin Raffel, Samuel S. Schoenholz, Maithra Raghu, Jascha Sohl-Dickstein

ICLR Workshop (2017)

Exploring the structure of a real-time, arbitrary neural artistic stylization network

Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens

Proceedings of the 28th British Machine Vision Conference (BMVC) (2017)

Generating High-Quality and Informative Conversation Responses with Sequence-to-Sequence Models

Louis Shao, Stephan Gouws, Denny Britz, Anna Goldie, Brian Strope, Ray Kurzweil

EMNLP (2017)

Geometry of 3D Environments and Sum of Squares Polynomials

Ameer Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani

arXiv (2017)

Geometry of Neural Network Loss Surfaces via Random Matrix Theory

Jeffrey Pennington, Yasaman Bahri

ICML (2017) (to appear)

Geometry-Based Next Frame Prediction from Monocular Video

Reza Mahjourian, Martin Wicke, Anelia Angelova

Intelligent Vehicles Symposium (2017)

Glimmers: Resolving the Privacy/Trust Quagmire

David Lie, Petros Maniatis

ACM Hot Topics in Operating Systems (HotOS), ACM SIGOPS, Whistler, British Columbia, Canada (2017)

HyperNetworks

David Ha, Andrew Dai, Quoc V. Le

ICLR (2017)

Identity Matters in Deep Learning

Moritz Hardt, Tengyu Ma

ICLR (2017)

Improving Policy Gradient by Exploring Under-appreciated Rewards

Ofir Nachum, Mohammad Norouzi, Dale Schuurmans

ICLR (2017)

Intelligible Language Modeling with Input Switched Affine Networks

Jakob N. Foerster, Justin Gilmer, Jan Chorowski, Jascha Sohl-Dickstein, David Sussillo

ICML (2017)

Large-Scale Evolution of Image Classifiers

Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Quoc Le, Alex Kurakin

ICML (2017)

Latent Sequence Decompositions

William Chan, Yu Zhang, Quoc Le, Navdeep Jaitly

ICLR (2017)

Learned Optimizers that Scale and Generalize

Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein

ICML (2017)

Learning Hard Alignments with Variational Inference

Dieterich Lawson, George Tucker, Chung-Cheng Chiu, Colin Raffel, Kevin Swersky, Navdeep Jaitly

arXiv (2017)

Learning a Natural Language Interface with Neural Programmer

Arvind Neelakantan, Quoc V. Le, Martin Abadi, Andrew McCallum, Dario Amodei

ICLR (2017)

Learning to Generate Long-term Future via Hierarchical Prediction

Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee

ICML (2017)

Learning to Remember Rare Events

Lukasz Kaiser, Ofir Nachum, Aurko Roy, Samy Bengio

ICLR (2017)

Learning to Skim Text

Adams Wei Yu, Hongrae Lee, Quoc V. Le

ACL (2017)

Learning with Proxy Supervision for End-To-End Visual Learning

Jiří Čermák, Anelia Angelova

Deep Learning for Vehicle Perception Workshop, Intelligent Vehicles Symposium (2017)

Massive Exploration of Neural Machine Translation Architectures

Denny Britz, Anna Goldie, Thang Luong, Quoc Le

arXiv (2017)

Neural Architecture Search with Reinforcement Learning

Barret Zoph, Quoc V. Le

ICLR (2017)

Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders

Jesse Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Douglas Eck, Karen Simonyan, Mohammad Norouzi

ICML (2017)

Neural Combinatorial Optimization with Reinforcement Learning

Irwan Bello, Hieu Pham, Quoc V. Le, Mohammad Norouzi, Samy Bengio

ICLR Workshop (2017)

Neural Message Passing for Quantum Chemistry

Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, George E. Dahl

arXiv (2017)

Neural Optimizer Search with Reinforcement Learning

Irwan Bello, Barret Zoph, Vijay Vasudevan, Quoc Le

ICML (2017) (to appear)

On the expressive power of deep neural net-works

Maithra Raghu, Ben Poole, Jon Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein

ICML (2017)

Online and Linear-Time Attention by Enforcing Monotonic Alignments

Colin Raffel, Douglas Eck, Peter Liu, Ron J. Weiss, Thang Luong

Thirty-fourth International Conference on Machine Learning (2017)

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean

ICLR (2017)

Particle Value Function

Chris Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Minh, Yee Whye Teh

ICLR Workshop (2017)

Path Integral Guided Policy Search

Yevgen Chebotar, Mrinal Kalakrishnan, Ali Yahya, Adrian Li, Stefan Schaal, Sergey Levine

IEEE International Conference on Robotics and Automation (2017)

PathNet: Evolution Channels Gradient Descent in Super Neural Networks

Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, Daan Wierstra

GECCO (2017)

PixColor: Pixel Recursive Colorization

Sergio Guadarrama, Ryan Dahl, David Bieber, Mohammad Norouzi, Jonathon Shlens, Kevin Murphy

Proceedings of the 28th British Machine Vision Conference (BMVC) (2017)

Pixel Recursive Super Resolution

Ryan Dahl, Mohammad Norouzi, Jonathan Shlens

arXiv (2017)

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic

Shixiang Gu, Timothy Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine

ICLR (2017)

REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models

George Tucker, Andriy Mnih, Chris J. Maddison, Jascha Sohl-Dickstein

ICLR Workshop (2017)

Random Features for Compositional Kernels

Amit Daniely, Roy Frostig, Vineet Gupta, Yoram Singer

arXiv (2017)

Regularizing Neural Networks by Penalizing Confident Output Distributions

Gabriel Pereyra, George Tucker, Jan Chorowski, Łukasz Kaiser, Geoffrey Hinton

ICLR Workshop (2017)

Robust Adversarial Reinforcement Learning

Lerrel Pinto, James Davidson, Rahul Sukthankar, Abhinav Gupta

ICML (2017)

SGD Learns the Conjugate Kernel Class of the Network

Amit Daniely

arXiv (2017)

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, Kunal Talwar

Proceedings of the International Conference on Learning Representations (2017)

Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control

Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck

ICML (2017)

Sequence-to-Sequence Models Can Directly Translate Foreign Speech

Ron J. Weiss, Jan Chorowski, Navdeep Jaitly, Yonghui Wu, Zhifeng Chen

Interspeech (2017)

Sharp Minima Can Generalize For Deep Nets

Laurent Dinh, Razvan Pascanu, Samy Bengio, Yoshua Bengio

ICML (2017)

Short and Deep: Sketching and Neural Networks

Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar

ICLR Workshop (2017)

Supervision via Competition: Robot Adversaries for Learning Tasks

Lerrel Pinto, James Davidson, Abhinav Gupta

ICRA (2017)

Surprising properties of dropout in deep networks

David P. Helmbold, Philip Long

COLT (2017)

Tacotron: Towards End-to-End Speech Synthesis

Yuxuan Wang, RJ Skerry-Ryan, Daisy Stanton, Yonghui Wu, Ron J. Weiss, Navdeep Jaitly, Zongheng Yang, Ying Xiao, Zhifeng Chen, Samy Bengio, Quoc Le, Yannis Agiomyrgiannakis, Rob Clark, Rif A. Saurous

Interspeech (2017)

The Space of Transferable Adversarial Examples

Florian Tramèr, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

arXiv (2017)

Time-Contrastive Networks: Self-Supervised Learning from Multi-View Observation

Pierre Sermanet, Corey Lynch, Jasmine Hsu, Sergey Levine

CVPR Workshop (2017)

Towards A Rigorous Science of Interpretable Machine Learning

Finale Doshi-Velez, Been Kim

arXiv (2017)

Towards Accurate Multi-person Pose Estimation in the Wild

George Papandreou, Tyler Zhu, Nori Kanazawa, Alexander Toshev, Jonathan Tompson, Chris Bregler, Kevin Murphy

CVPR (2017)

Towards better decoding and language model integration in sequence to sequence models

Jan Chorowski, Navdeep Jaitly

Interspeech (2017)

Training a Subsampling Mechanism in Expectation

Colin Raffel, Dieterich Lawson

ICLR Workshop (2017)

Tuning Recurrent Neural Networks With Reinforcement Learning

Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, Jose Miguel Hernandez Lobato, Richard E. Turner, Doug Eck

ICLR Workshop (2017)

Understanding deep learning requires rethinking generalization

Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals

ICLR (2017)

Unrolled Generative Adversarial Networks

Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein

ICLR (2017)

Unsupervised Perceptual Rewards for Imitation Learning

Pierre Sermanet, Kelvin Xu, Sergey Levine

RSS (2017)

Unsupervised Pixel-level Domain Adaptation with GANs

Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan

CVPR (2017)

Variational Boosting: Iteratively Refining Posterior Approximations

Andrew C. Miller, Nicholas Foti, Ryan P. Adams

ICML (2017)

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning

Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kholi

ICML (2017)

A Neural Transducer

Navdeep Jaitly, David Sussillo, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, Samy Bengio

NIPS 2016 (2016)

Adversarial Autoencoders

Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow

International Conference on Learning Representations (2016)

Adversarial Evaluation of Dialogue Models

Anjuli Kannan, Oriol Vinyals

NIPS Workshop (2016)

An Online Sequence-to-Sequence Model Using Partial Conditioning

Navdeep Jaitly, Quoc V. Le, Oriol Vinyals, Samy Bengio

ARXIV (2016)

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton

NIPS (2016)

Audio Deepdream: Optimizing raw audio with convolutional networks.

Adam Roberts, Cinjon Resnick, Diego Ardila, Doug Eck

International Society for Music Information Retrieval Conference, Google Brain (2016)

Chained predictions using convolutional neural networks

Georgia Gkioxari, Alexander Toshev, Navdeep Jaitly

ECCV (2016)

Collective Entity Resolution with Multi-Focal Attention

Amir Globerson, Nevena Lazic, Soumen Chakrabarti, Amarnag Subramanya, Michael Ringaard, Fernando Pereira

ACL (2016)

Continuous Deep Q-Learning with Model-based Acceleration

Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine

International Conference on Machine Learning (2016)

Deep Learning Games

Dale Schuurmans, Martin Zinkevich

NIPS 2016 (2016)

Deep Learning with Differential Privacy

Martin Abadi, Andy Chu, Ian Goodfellow, Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang

23rd ACM Conference on Computer and Communications Security (ACM CCS) (2016), pp. 308-318

DeepMath - Deep Sequence Models for Premise Selection

Alex A. Alemi, Francois Chollet, Geoffrey Irving, Christian Szegedy, Josef Urban

NIPS (2016)

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros, Ramasamy Kim, Rajiv Raman, Philip Q Nelson, Jessica Mega, Dale Webster

JAMA (2016)

Domain Separation Networks

Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan

NIPS 2016 (2016)

End-to-End Text-Dependent Speaker Verification

Georg Heigold, Ignacio Moreno, Samy Bengio, Noam M. Shazeer

International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE (2016)

Equality of Opportunity in Supervised Learning

Moritz Hardt, Eric Price, Nathan Srebro

arXiv (2016)

Exploring the limits of language modeling

Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, Yonghui Wu

Google Inc. (2016)

Exponential expressivity in deep neural networks through transient chaos

Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli

NIPS 2016 (2016)

Generating Music by Fine-Tuning Recurrent Neural Networks with Reinforcement Learning

Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck

Deep Reinforcement Learning Workshop, NIPS (2016)

Generating Sentences from a Continuous Space

Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, Samy Bengio

CoNLL (2016)

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean

CoRR, vol. abs/1609.08144 (2016)

Improved generator objectives for GANs

Alex Alemi, Anelia Angelova, Ben Poole, Jascha Sohl-dickstein

NIPS Workshop on Adversarial Learning (2016)

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex A. Alemi

ICLR 2016 Workshop

Incremental, iterative data processing with timely dataflow

Derek G. Murray, Frank McSherry, Michael Isard, Rebecca Isaacs, Paul Barham, Martin Abadi

Communications of the ACM, vol. 59 (2016), pp. 75-83

Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection

Sergey Levine, Peter Pastor Sampedro, Alex Krizhevsky, Deirdre Quillen

International Symposium on Experimental Robotics (2016)

Learning to Protect Communications with Adversarial Neural Cryptography

Martín Abadi, David G. Andersen

arXiv (2016)

Listen, Attend and Spell: A Neural Network for Large Vocabulary Conversational Speech Recognition

William Chan, Navdeep Jaitly, Quoc V. Le, Oriol Vinyals

ICASSP (2016)

Mastering the game of Go with deep neural networks and tree search

David Silver, Aja Huang, Christopher J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis

Nature, vol. 529 (2016), pp. 484-503

MuProp: Unbiased Backpropagation for Stochastic Neural Networks

Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih

International Conference on Learning Representations (2016)

Multi-task Sequence to Sequence Learning

Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser

International Conference on Learning Representations (2016)

Multilingual Language Processing From Bytes

Dan Gillick, Cliff Brunk, Oriol Vinyals, Amarnag Subramanya

NAACL (2016)

Net2Net: Accelerating Learning via Knowledge Transfer

Tianqi Chen, Ian Goodfellow, Jonathon Shlens

International Conference on Learning Representations (2016)

Neural GPUs Learn Algorithms

Lukasz Kaiser, Ilya Sutskever

International Conference on Learning Representations (2016)

Neural Programmer: Inducing Latent Programs with Gradient Descent

arvind neelakantan, Quoc V. Le, Ilya Sutskever

International Conference on Learning Representations (2016)

Neural Random-Access Machines

Karol Kurach, Marcin Andrychowicz, Ilya Sutskever

ICLR (2016)

Order matters: Sequence to sequence for sets

Oriol Vinyals, Samy Bengio, Manjunath Kudlur

International Conference on Learning Representations (ICLR) (2016)

Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision

Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee

NIPS (2016)

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (2016)

Revisiting Distributed Synchronous SGD

Jianmin Chen, Rajat Monga, Samy Bengio, Rafal Jozefowicz

International Conference on Learning Representations Workshop Track (2016)

Reward Augmented Maximum Likelihood for Neural Structured Prediction

Mohammad Norouzi, Samy Bengio, Zhifeng Chen, Navdeep Jaitly, Mike Schuster, Yonghui Wu, Dale Schuurmans

NIPS (2016)

Smart Reply: Automated Response Suggestion for Email

Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufman, Balint Miklos, Greg Corrado, Andrew Tomkins, Laszlo Lukacs, Marina Ganea, Peter Young, Vivek Ramavajjala

Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (2016).

TensorFlow: A system for large-scale machine learning

Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16), USENIX Association (2016), pp. 265-283

TensorFlow: Learning Functions at Scale

Martin Abadi

ICFP (2016)

The Applied Pi Calculus: Mobile Values, New Names, and Secure Communication

Martin Abadi, Bruno Blanchet, Cedric Fournet

arXiv (2016)

The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition

Jonathan Krause, Andrew Howard, Benjamin Sapp, Howard Zhou, Alexander Toshev, Tom Duerig, James Philbin, Li Fei-Fei

Computer Vision and Pattern Recognition (2016)

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity

Amit Daniely, Roy Frostig, Yoram Singer

NIPS 2016 (2016)

Unsupervised Learning for Physical Interaction through Video Prediction

Chelsea Finn, Ian Goodfellow, Sergey Levine

arXiv e-prints (2016)

Unsupervised Pretraining for Sequence to Sequence Learning

Prajit Ramachandran, Peter J. Liu, Quoc V. Le

arXiv (2016)

Using Fast Weights to Attend to the Recent Past

Jimmy Ba, Geoffrey Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu

Google (2016)

Virtual Adversarial Training for Semi-Supervised Text Classification

Takeru Miayto, Andrew M. Dai, Ian Goodfellow

arXiv preprint (2016)

A Neural Conversational Model

Oriol Vinyals, Quoc V. Le

ICML Deep Learning Workshop (2015)

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

CoRR, vol. abs/1504.00941 (2015)

A Unified Approach to Boundedness Properties in MSO

Lukasz Kaiser, Martin Lang 0001, Simon Leßenich, Christof Löding

CSL (2015), pp. 441-456

Adding Gradient Noise Improves Learning for Very Deep Networks

arvind neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens

CoRR, vol. abs/1511.06807 (2015)

Addressing the Rare Word Problem in Neural Machine Translation

Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba

ACL (2015)

An empirical exploration of recurrent network architectures

Rafal Jozefowicz, Wojciech Zaremba, Ilya Sutskever

Journal of Machine Learning Research (2015)

Attention for fine-grained categorization

Pierre Sermanet, Andrea Frome, Esteban Real

International Conference on Learning Representations (ICLR) workshop, Arxiv (2015)

Beyond Short Snippets: Deep Networks for Video Classification

Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici

Computer Vision and Pattern Recognition (2015)

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

Stephan Gouws, Yoshua Bengio, Greg Corrado

Proceedings of the 32nd International Conference on Machine Learning (2015)

Characterising Choiceless Polynomial Time with First-Order Interpretations

Erich Grädel, Wied Pakusa, Svenja Schalthöfer, Lukasz Kaiser

LICS (2015), pp. 677-688

Convolutional, Long Short-Term Memory, Fully Connected Deep Neural Networks

Tara Sainath, Oriol Vinyals, Andrew Senior, Hasim Sak

ICASSP (2015)

Deep Networks With Large Output Spaces

Sudheendra Vijayanarasimhan, Jonathon Shlens, Rajat Monga, Jay Yagnik

International Conference on Learning Representations (2015)

Distilling the Knowledge in a Neural Network

Geoffrey Hinton, Oriol Vinyals, Jeffrey Dean

NIPS Deep Learning and Representation Learning Workshop (2015)

Explaining and Harnessing Adversarial Examples

Ian Goodfellow, Jonathon Shlens, Christian Szegedy

International Conference on Learning Representations (2015)

Going Deeper with Convolutions

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich

Computer Vision and Pattern Recognition (CVPR) (2015)

Grammar as a Foreign Language

Oriol Vinyals, Lukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey Hinton

NIPS (2015)

Graph Searching Games and Width Measures for Directed Graphs

Saeed Akhoondian Amiri, Lukasz Kaiser, Stephan Kreutzer, Roman Rabinovich, Sebastian Siebertz

STACS (2015), pp. 34-47

Guest Editorial: Deep Learning

Marc'Aurelio Ranzato, Geoffrey E. Hinton, Yann LeCun

International Journal of Computer Vision, vol. 113 (2015), pp. 1-2

Learning semantic relationships for better action retrieval in images

Vignesh Ramanathan, Congcong Li, Jia Deng, Wei Han, Zhen Li, Kunlong Gu, Yang Song, Samy Bengio, Chuck Rosenberg, Li Fei-Fei

CVPR (2015)

Learning the Speech Front-end with Raw Waveform CLDNNs

Tara Sainath, Ron J. Weiss, Kevin Wilson, Andrew W. Senior, Oriol Vinyals

Interspeech (2015)

Learning to Execute

Wojciech Zaremba, Ilya Sutskever

arXiv (2015)

Move evaluation in go using deep convolutional neural networks

Chris J. Maddison, Aja Huang, Ilya Sutskever, David Silver

ICLR (2015)

Pedestrian Detection with a Large-Field-Of-View Deep Network

Anelia Angelova, Alex Krizhevsky, Vincent Vanhoucke

Proceedings of ICRA 2015

Pointer Networks

Oriol Vinyals, Meire Fortunato, Navdeep Jaitly

NIPS (2015), pp. 2692-2700

Qualitatively Characterizing Neural Network Optimization Problems

Ian Goodfellow, Oriol Vinyals, Andrew Saxe

International Conference on Learning Representations (2015)

Real-Time Grasp Detection Using Convolutional Neural Networks

Joseph Redmon, Anelia Angelova

International Conference on Robotics and Automation (ICRA), IEEE (2015)

Real-Time Pedestrian Detection With Deep Network Cascades

Anelia Angelova, Alex Krizhevsky, Vincent Vanhoucke, Abhijit Ogale, Dave Ferguson

Proceedings of BMVC 2015

Reinforcement learning neural Turing machines

Wojciech Zaremba, Ilya Sutskever

Google Inc. (2015)

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

Samy Bengio, Oriol Vinyals, Navdeep Jaitly, Noam M. Shazeer

Advances in Neural Information Processing Systems, NIPS (2015)

Semi-supervised sequence learning

Andrew M. Dai, Quoc V. Le

Advances in Neural Information Processing Systems, NIPS (2015)

Sentence Compression by Deletion with LSTMs

Katja Filippova, Enrique Alfonseca, Carlos Colmenares, Lukasz Kaiser, Oriol Vinyals

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP'15)

Show and tell: A neural image caption generator

Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan

Computer Vision and Pattern Recognition (2015)

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

tensorflow.org (2015)

Towards Principled Unsupervised Learning

Ilya Sutskever, Rafal Jozefowicz, Karol Gregor, Danilo Rezende, Tim Lillicrap, Oriol Vinyals

Google Inc. (2015)

Training Deep Neural Networks on Noisy Labels with Bootstrapping

Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich

ICLR 2015

Asynchronous Stochastic Optimization for Sequence Training of Deep Neural Networks

Georg Heigold, Erik McDermott, Vincent Vanhoucke, Andrew Senior, Michiel Bacchiani

Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE, Firenze, Italy (2014)

Autoregressive Product of Multi-frame Predictions Can Improve the Accuracy of Hybrid Models

Navdeep Jaitly, Vincent Vanhoucke, Geoffrey Hinton

Proceedings of Interspeech 2014

Distributed Representations of Sentences and Documents

Quoc V. Le, Tomas Mikolov

International Conference on Machine Learning (2014)

Intriguing properties of neural networks

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, Rob Fergus

International Conference on Learning Representations (2014)

Large-Scale Object Classification Using Label Relation Graphs

Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig Adam

European Conference on Computer Vision (2014)

Learning Factored Representations in a Deep Mixture of Experts

David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever

ICLR Workshop (2014)

Local Collaborative Ranking

Joonseok Lee, Samy Bengio, Seungyeon Kim, Guy Lebanon, Yoram Singer

Proceedings of the 23rd International World Wide Web Conference (WWW), ACM (2014)

On Learning Where to Look

Marc'Aurelio Ranzato

Google Inc. (2014)

Random Walk Initialization for Training Very Deep Feedforward Networks

David Sussillo, L.F. Abbott

arXiv preprint, Google Inc. (2014), pp. 1-10

Recurrent Neural Network Regularization

Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals

Google Inc. (2014)

Sequence Discriminative Distributed Training of Long Short-Term Memory Recurrent Neural Networks

Hasim Sak, Oriol Vinyals, Georg Heigold, Andrew Senior, Erik McDermott, Rajat Monga, Mark Mao

Interspeech (2014)

Sequence to Sequence Learning with Neural Networks

Ilya Sutskever, Oriol Vinyals, Quoc V. Le

Proc. NIPS, Montreal, CA (2014)

Training Highly Multi-class Linear Classifiers

Maya R. Gupta, Samy Bengio, Jason Weston

Journal Machine Learning Research (JMLR) (2014), 1461-−1492

Word Embeddings for Speech Recognition

Samy Bengio, Georg Heigold

Proceedings of the 15th Conference of the International Speech Communication Association, Interspeech (2014)

Zero-Shot Learning by Convex Combination of Semantic Embeddings

Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean

International Conference on Learning Representations (2014)

An Empirical study of learning rates in deep neural networks for speech recognition

Andrew Senior, Georg Heigold, Marc'aurelio Ranzato, Ke Yang

Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE, Vancouver, CA (2013) (to appear)

DeViSE: A Deep Visual-Semantic Embedding Model

Andrea Frome, Greg Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc’Aurelio Ranzato, Tomas Mikolov

Neural Information Processing Systems (NIPS) (2013)

Distributed Representations of Words and Phrases and their Compositionality

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean

Neural and Information Processing System (NIPS) (2013)

Efficient Estimation of Word Representations in Vector Space

Tomas Mikolov, Kai Chen, Greg S. Corrado, Jeffrey Dean

International Conference on Learning Representations (2013)

Exploiting Similarities among Languages for Machine Translation

Tomas Mikolov, Quoc V. Le, Ilya Sutskever

ARXIV (2013)

Fastfood-computing hilbert space expansions in loglinear time

Quoc V. Le, Tamas Sarlos, Alex Smola

International Conference on Machine Learning (2013) (to appear)

Grounded compositional semantics for finding and describing images with sentences

Richard Socher, Andrej Karpathy, Quoc V. Le, Chris D. Manning, Andrew Y. Ng

Transactions of the Association for Computational Linguistics (2013) (to appear)

Multiframe Deep Neural Networks for Acoustic Modeling

Vincent Vanhoucke, Matthieu Devin, Georg Heigold

Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE, Vancouver, CA (2013)

Multilingual acoustic models using distributed deep neural networks

Georg Heigold, Vincent Vanhoucke, Andrew Senior, Patrick Nguyen, Marc'aurelio Ranzato, Matthieu Devin, Jeff Dean

Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE, Vancouver, CA (2013)

On Rectified Linear Units For Speech Processing

M.D. Zeiler, M. Ranzato, R. Monga, M. Mao, K. Yang, Q.V. Le, P. Nguyen, A. Senior, V. Vanhoucke, J. Dean, G.E. Hinton

38th International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver (2013)

One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling

Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, Tony Robinson

ArXiv, Google (2013)

Using Web Co-occurrence Statistics for Improving Image Categorization

Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer

arXiv (2013)

Application Of Pretrained Deep Neural Networks To Large Vocabulary Speech Recognition

Navdeep Jaitly, Patrick Nguyen, Andrew Senior, Vincent Vanhoucke

Proceedings of Interspeech 2012

Building high-level features using large scale unsupervised learning

Quoc Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg Corrado, Jeff Dean, Andrew Ng

International Conference in Machine Learning (2012)

Deep Neural Networks for Acoustic Modeling in Speech Recognition

Geoffrey Hinton, Li Deng, Dong Yu, George Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara Sainath, Brian Kingsbury

Signal Processing Magazine (2012)

Large Scale Distributed Deep Networks

Jeffrey Dean, Greg S. Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc’Aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, Andrew Y. Ng

NIPS (2012)