Geoffrey E. Hinton

Publication Activity (10 Years)

Years Active: 1976-2023
Publications (10 Years): 78

Top Venues

CoRR

NeurIPS

ICML

ICLR

University of Edinburgh, UK (PHD)

Education History

University of Edinburgh, UK

PHD

Publications

Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton
Scaling Forward Gradient With Local Losses. ICLR (2023)
Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann
Managing AI Risks in an Era of Rapid Progress. CoRR (2023)
Ting Chen, Ruixiang Zhang, Geoffrey E. Hinton
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning. ICLR (2023)
Geoffrey E. Hinton
How to Represent Part-Whole Hierarchies in a Neural Network. Neural Comput. 35 (3) (2023)
Ting Chen, Lala Li, Saurabh Saxena, Geoffrey E. Hinton, David J. Fleet
A Generalist Framework for Panoptic Segmentation of Images and Videos. ICCV (2023)
Shekoofeh Azizi, Laura Culp, Jan Freyberg, Basil Mustafa, Sebastien Baur, Simon Kornblith, Ting Chen, Patricia MacWilliams, S. Sara Mahdavi, Ellery Wulczyn, Boris Babenko, Megan Wilson, Aaron Loh, Po-Hsuan Cameron Chen, Yuan Liu, Pinal Bavishi, Scott Mayer McKinney, Jim Winkens, Abhijit Guha Roy, Zachary Beaver, Fiona Ryan, Justin Krogue, Mozziyar Etemadi, Umesh Telang, Yun Liu, Lily Peng, Gregory S. Corrado, Dale R. Webster, David J. Fleet, Geoffrey E. Hinton, Neil Houlsby, Alan Karthikesalingam, Mohammad Norouzi, Vivek Natarajan
Robust and Efficient Medical Imaging with Self-Supervision. CoRR (2022)
Renjie Liao, Simon Kornblith, Mengye Ren, David J. Fleet, Geoffrey E. Hinton
Gaussian-Bernoulli RBMs Without Tears. CoRR (2022)
Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, Geoffrey E. Hinton
Pix2seq: A Language Modeling Framework for Object Detection. ICLR (2022)
Geoffrey E. Hinton
The Forward-Forward Algorithm: Some Preliminary Investigations. CoRR (2022)
Ting Chen, Ruixiang Zhang, Geoffrey E. Hinton
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning. CoRR (2022)
Laura Culp, Sara Sabour, Geoffrey E. Hinton
Testing GLOM's ability to infer wholes from ambiguous parts. CoRR (2022)
Ting Chen, Lala Li, Saurabh Saxena, Geoffrey E. Hinton, David J. Fleet
A Generalist Framework for Panoptic Segmentation of Images and Videos. CoRR (2022)
Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton
Scaling Forward Gradient With Local Losses. CoRR (2022)
Kevin Clark, Kelvin Guu, Ming-Wei Chang, Panupong Pasupat, Geoffrey E. Hinton, Mohammad Norouzi
Meta-Learning Fast Weight Language Models. EMNLP (2022)
Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton
A Unified Sequence Interface for Vision Tasks. CoRR (2022)
Kevin Clark, Kelvin Guu, Ming-Wei Chang, Panupong Pasupat, Geoffrey E. Hinton, Mohammad Norouzi
Meta-Learning Fast Weight Language Models. CoRR (2022)
Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton
A Unified Sequence Interface for Vision Tasks. NeurIPS (2022)
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton
Teaching with Commentaries. ICLR (2021)
Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, Geoffrey E. Hinton
Pix2seq: A Language Modeling Framework for Object Detection. CoRR (2021)
Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton
Neural Additive Models: Interpretable Machine Learning with Neural Nets. NeurIPS (2021)
Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey E. Hinton, David J. Fleet
Unsupervised Part Representation by Flow Capsules. ICML (2021)
Geoffrey E. Hinton
How to represent part-whole hierarchies in a neural network. CoRR (2021)
Yoshua Bengio, Yann LeCun, Geoffrey E. Hinton
Deep learning for AI. Commun. ACM 64 (7) (2021)
Weiwei Sun, Andrea Tagliasacchi, Boyang Deng, Sara Sabour, Soroosh Yazdani, Geoffrey E. Hinton, Kwang Moo Yi
Canonical Capsules: Self-Supervised Capsules in Canonical Pose. NeurIPS (2021)
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton
Big Self-Supervised Models are Strong Semi-Supervised Learners. NeurIPS (2020)
Yao Qin, Nicholas Frosst, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton
Deflecting Adversarial Attacks. CoRR (2020)
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton
A Simple Framework for Contrastive Learning of Visual Representations. ICML (2020)
Rishabh Agarwal, Nicholas Frosst, Xuezhou Zhang, Rich Caruana, Geoffrey E. Hinton
Neural Additive Models: Interpretable Machine Learning with Neural Nets. CoRR (2020)
William Chan, Chitwan Saharia, Geoffrey E. Hinton, Mohammad Norouzi, Navdeep Jaitly
Imputer: Sequence Modelling via Imputation and Dynamic Programming. ICML (2020)
Geoffrey E. Hinton
The Next Generation of Neural Networks. SIGIR (2020)
Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey E. Hinton, David J. Fleet
Unsupervised part representation by Flow Capsules. CoRR (2020)
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey E. Hinton, Andrea Tagliasacchi
CvxNet: Learnable Convex Decomposition. CVPR (2020)
Weiwei Sun, Andrea Tagliasacchi, Boyang Deng, Sara Sabour, Soroosh Yazdani, Geoffrey E. Hinton, Kwang Moo Yi
Canonical Capsules: Unsupervised Capsules in Canonical Pose. CoRR (2020)
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
Subclass Distillation. CoRR (2020)
William Chan, Chitwan Saharia, Geoffrey E. Hinton, Mohammad Norouzi, Navdeep Jaitly
Imputer: Sequence Modelling via Imputation and Dynamic Programming. CoRR (2020)
Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions. ICLR (2020)
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton
Big Self-Supervised Models are Strong Semi-Supervised Learners. CoRR (2020)
Boyang Deng, John P. Lewis, Timothy Jeruzalski, Gerard Pons-Moll, Geoffrey E. Hinton, Mohammad Norouzi, Andrea Tagliasacchi
NASA Neural Articulated Shape Approximation. ECCV (7) (2020)
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton
A Simple Framework for Contrastive Learning of Visual Representations. CoRR (2020)
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton
Teaching with Commentaries. CoRR (2020)
Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton
Stacked Capsule Autoencoders. NeurIPS (2019)
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
When Does Label Smoothing Help? CoRR (2019)
Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton
Similarity of Neural Network Representations Revisited. CoRR (2019)
Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton
Similarity of Neural Network Representations Revisited. ICML (2019)
Aidan N. Gomez, Ivan Zhang, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton
Learning Sparse Networks Using Targeted Dropout. CoRR (2019)
Nicholas Frosst, Nicolas Papernot, Geoffrey E. Hinton
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss. CoRR (2019)
Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba
Lookahead Optimizer: k steps forward, 1 step back. CoRR (2019)
Nicholas Frosst, Nicolas Papernot, Geoffrey E. Hinton
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss. ICML (2019)
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
When does label smoothing help? NeurIPS (2019)
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey E. Hinton, Andrea Tagliasacchi
CvxNets: Learnable Convex Decomposition. CoRR (2019)
Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton
Stacked Capsule Autoencoders. CoRR (2019)
Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
Lookahead Optimizer: k steps forward, 1 step back. NeurIPS (2019)
Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions. CoRR (2019)
Timothy Jeruzalski, Boyang Deng, Mohammad Norouzi, John P. Lewis, Geoffrey E. Hinton, Andrea Tagliasacchi
NASA: Neural Articulated Shape Approximation. CoRR (2019)
Boyang Deng, Simon Kornblith, Geoffrey E. Hinton
Cerberus: A Multi-headed Derenderer. CoRR (2019)
Sergey Bartunov, Adam Santoro, Blake A. Richards, Geoffrey E. Hinton, Timothy P. Lillicrap
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures. CoRR (2018)
Geoffrey E. Hinton, Sara Sabour, Nicholas Frosst
Matrix capsules with EM routing. ICLR (Poster) (2018)
Jamie Ryan Kiros, William Chan, Geoffrey E. Hinton
Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search. ACL (1) (2018)
Rohan Anil, Gabriel Pereyra, Alexandre Passos, Róbert Ormándi, George E. Dahl, Geoffrey E. Hinton
Large scale distributed neural network training through online distillation. CoRR (2018)
Rohan Anil, Gabriel Pereyra, Alexandre Passos, Róbert Ormándi, George E. Dahl, Geoffrey E. Hinton
Large scale distributed neural network training through online distillation. ICLR (Poster) (2018)
Melody Y. Guan, Varun Gulshan, Andrew M. Dai, Geoffrey E. Hinton
Who Said What: Modeling Individual Labelers Improves Classification. AAAI (2018)
Nicholas Frosst, Sara Sabour, Geoffrey E. Hinton
DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules. CoRR (2018)
Sergey Bartunov, Adam Santoro, Blake A. Richards, Luke Marris, Geoffrey E. Hinton, Timothy P. Lillicrap
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures. NeurIPS (2018)
Nicholas Frosst, Geoffrey E. Hinton
Distilling a Neural Network Into a Soft Decision Tree. CoRR (2017)
Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton
ImageNet classification with deep convolutional neural networks. Commun. ACM 60 (6) (2017)
Gabriel Pereyra, George Tucker, Jan Chorowski, Lukasz Kaiser, Geoffrey E. Hinton
Regularizing Neural Networks by Penalizing Confident Output Distributions. CoRR (2017)
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. ICLR (Poster) (2017)
Sara Sabour, Nicholas Frosst, Geoffrey E. Hinton
Dynamic Routing Between Capsules. CoRR (2017)
Nicholas Frosst, Geoffrey E. Hinton
Distilling a Neural Network Into a Soft Decision Tree. CEx@AI*IA (2017)
Gabriel Pereyra, George Tucker, Jan Chorowski, Lukasz Kaiser, Geoffrey E. Hinton
Regularizing Neural Networks by Penalizing Confident Output Distributions. ICLR (Workshop) (2017)
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. CoRR (2017)
Melody Y. Guan, Varun Gulshan, Andrew M. Dai, Geoffrey E. Hinton
Who Said What: Modeling Individual Labelers Improves Classification. CoRR (2017)
Sara Sabour, Nicholas Frosst, Geoffrey E. Hinton
Dynamic Routing Between Capsules. NIPS (2017)
S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. NIPS (2016)
S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, Geoffrey E. Hinton
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. CoRR (2016)
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
Using Fast Weights to Attend to the Recent Past. NIPS (2016)
Lei Jimmy Ba, Jamie Ryan Kiros, Geoffrey E. Hinton
Layer Normalization. CoRR (2016)
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
Using Fast Weights to Attend to the Recent Past. CoRR (2016)
Oriol Vinyals, Lukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey E. Hinton
Grammar as a Foreign Language. NIPS (2015)
Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton
Deep learning. Nat. 521 (7553) (2015)
Geoffrey E. Hinton, Oriol Vinyals, Jeffrey Dean
Distilling the Knowledge in a Neural Network. CoRR (2015)
Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units. CoRR (2015)
Marc'Aurelio Ranzato, Geoffrey E. Hinton, Yann LeCun
Guest Editorial: Deep Learning. Int. J. Comput. Vis. 113 (1) (2015)
Navdeep Jaitly, Vincent Vanhoucke, Geoffrey E. Hinton
Autoregressive product of multi-frame predictions can improve the accuracy of hybrid models. INTERSPEECH (2014)
Oriol Vinyals, Lukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey E. Hinton
Grammar as a Foreign Language. CoRR (2014)
Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov
Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15 (1) (2014)
Ruhi Sarikaya, Geoffrey E. Hinton, Anoop Deoras
Application of Deep Belief Networks for Natural Language Understanding. IEEE ACM Trans. Audio Speech Lang. Process. 22 (4) (2014)
Geoffrey E. Hinton
Where Do Features Come From? Cogn. Sci. 38 (6) (2014)
Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton
Modeling Natural Images Using Gated MRFs. IEEE Trans. Pattern Anal. Mach. Intell. 35 (9) (2013)
Alex Graves, Abdel-rahman Mohamed, Geoffrey E. Hinton
Speech recognition with deep recurrent neural networks. ICASSP (2013)
Ilya Sutskever, James Martens, George E. Dahl, Geoffrey E. Hinton
On the importance of initialization and momentum in deep learning. ICML (3) (2013)
George E. Dahl, Tara N. Sainath, Geoffrey E. Hinton
Improving deep neural networks for LVCSR using rectified linear units and dropout. ICASSP (2013)
Navdeep Jaitly, Geoffrey E. Hinton
Using an autoencoder with deformable templates to discover features for automated speech recognition. INTERSPEECH (2013)
Nitish Srivastava, Ruslan Salakhutdinov, Geoffrey E. Hinton
Modeling Documents with Deep Boltzmann Machines. CoRR (2013)
Nitish Srivastava, Ruslan Salakhutdinov, Geoffrey E. Hinton
Modeling Documents with Deep Boltzmann Machines. UAI (2013)
Li Deng, Geoffrey E. Hinton, Brian Kingsbury
New types of deep neural network learning for speech recognition and related applications: an overview. ICASSP (2013)
Geoffrey E. Hinton, Yee Whye Teh
Discovering Multiple Constraints that are Frequently Approximately Satisfied CoRR (2013)
Matthew D. Zeiler, Marc'Aurelio Ranzato, Rajat Monga, Mark Z. Mao, K. Yang, Quoc Viet Le, Patrick Nguyen, Andrew W. Senior, Vincent Vanhoucke, Jeffrey Dean, Geoffrey E. Hinton
On rectified linear units for speech processing. ICASSP (2013)
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton
Tensor Analyzers. ICML (3) (2013)
Alex Graves, Abdel-rahman Mohamed, Geoffrey E. Hinton
Speech Recognition with Deep Recurrent Neural Networks CoRR (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Geoffrey E. Hinton