Geoffrey E. Hinton

Affiliations:
  • Google DeepMind, London, UK
  • University of Toronto, Department of Computer Science, ON, Canada


According to our database1, Geoffrey E. Hinton authored at least 261 papers between 1976 and 2023.

Collaborative distances:

Awards

Turing Prize recipient

Turing Prize 2018, "For conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing." awarded to Yoshua Bengio and Geoffrey E. Hinton and Yann LeCun.

ACM Fellow

ACM Fellow 2023, "For conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing".

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2023
How to Represent Part-Whole Hierarchies in a Neural Network.
Neural Comput., March, 2023

Managing AI Risks in an Era of Rapid Progress.
CoRR, 2023

Scaling Forward Gradient With Local Losses.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Generalist Framework for Panoptic Segmentation of Images and Videos.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
The Forward-Forward Algorithm: Some Preliminary Investigations.
CoRR, 2022

Testing GLOM's ability to infer wholes from ambiguous parts.
CoRR, 2022

Gaussian-Bernoulli RBMs Without Tears.
CoRR, 2022

A Generalist Framework for Panoptic Segmentation of Images and Videos.
CoRR, 2022

Robust and Efficient Medical Imaging with Self-Supervision.
CoRR, 2022

A Unified Sequence Interface for Vision Tasks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Pix2seq: A Language Modeling Framework for Object Detection.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Learning Fast Weight Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
Deep learning for AI.
Commun. ACM, 2021

Canonical Capsules: Self-Supervised Capsules in Canonical Pose.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Additive Models: Interpretable Machine Learning with Neural Nets.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Unsupervised Part Representation by Flow Capsules.
Proceedings of the 38th International Conference on Machine Learning, 2021

Teaching with Commentaries.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Canonical Capsules: Unsupervised Capsules in Canonical Pose.
CoRR, 2020

Neural Additive Models: Interpretable Machine Learning with Neural Nets.
CoRR, 2020

Deflecting Adversarial Attacks.
CoRR, 2020

Subclass Distillation.
CoRR, 2020

The Next Generation of Neural Networks.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Big Self-Supervised Models are Strong Semi-Supervised Learners.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Simple Framework for Contrastive Learning of Visual Representations.
Proceedings of the 37th International Conference on Machine Learning, 2020

Imputer: Sequence Modelling via Imputation and Dynamic Programming.
Proceedings of the 37th International Conference on Machine Learning, 2020

Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions.
Proceedings of the 8th International Conference on Learning Representations, 2020

NASA Neural Articulated Shape Approximation.
Proceedings of the Computer Vision - ECCV 2020, 2020

CvxNet: Learnable Convex Decomposition.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
NASA: Neural Articulated Shape Approximation.
CoRR, 2019

CvxNets: Learnable Convex Decomposition.
CoRR, 2019

Learning Sparse Networks Using Targeted Dropout.
CoRR, 2019

Cerberus: A Multi-headed Derenderer.
CoRR, 2019

Lookahead Optimizer: k steps forward, 1 step back.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

When does label smoothing help?
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stacked Capsule Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Similarity of Neural Network Representations Revisited.
Proceedings of the 36th International Conference on Machine Learning, 2019

Analyzing and Improving Representations with the Soft Nearest Neighbor Loss.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules.
CoRR, 2018

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.
CoRR, 2018

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Matrix capsules with EM routing.
Proceedings of the 6th International Conference on Learning Representations, 2018

Large scale distributed neural network training through online distillation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Who Said What: Modeling Individual Labelers Improves Classification.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Deep Belief Nets.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Boltzmann Machines.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

ImageNet classification with deep convolutional neural networks.
Commun. ACM, 2017

Dynamic Routing Between Capsules.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.
Proceedings of the 5th International Conference on Learning Representations, 2017

Regularizing Neural Networks by Penalizing Confident Output Distributions.
Proceedings of the 5th International Conference on Learning Representations, 2017

Distilling a Neural Network Into a Soft Decision Tree.
Proceedings of the First International Workshop on Comprehensibility and Explanation in AI and ML 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017

2016
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.
CoRR, 2016

Layer Normalization.
CoRR, 2016

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Using Fast Weights to Attend to the Recent Past.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Deep learning.
Nat., 2015

Guest Editorial: Deep Learning.
Int. J. Comput. Vis., 2015

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units.
CoRR, 2015

Distilling the Knowledge in a Neural Network.
CoRR, 2015

Grammar as a Foreign Language.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Application of Deep Belief Networks for Natural Language Understanding.
IEEE ACM Trans. Audio Speech Lang. Process., 2014

Dropout: a simple way to prevent neural networks from overfitting.
J. Mach. Learn. Res., 2014

Where Do Features Come From?
Cogn. Sci., 2014

Autoregressive product of multi-frame predictions can improve the accuracy of hybrid models.
Proceedings of the INTERSPEECH 2014, 2014

2013
Modeling Natural Images Using Gated MRFs.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Modeling Documents with Deep Boltzmann Machines.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Using an autoencoder with deformable templates to discover features for automated speech recognition.
Proceedings of the INTERSPEECH 2013, 2013

Tensor Analyzers.
Proceedings of the 30th International Conference on Machine Learning, 2013

On the importance of initialization and momentum in deep learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

On rectified linear units for speech processing.
Proceedings of the IEEE International Conference on Acoustics, 2013

Speech recognition with deep recurrent neural networks.
Proceedings of the IEEE International Conference on Acoustics, 2013

New types of deep neural network learning for speech recognition and related applications: an overview.
Proceedings of the IEEE International Conference on Acoustics, 2013

Improving deep neural networks for LVCSR using rectified linear units and dropout.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
A Practical Guide to Training Restricted Boltzmann Machines.
Proceedings of the Neural Networks: Tricks of the Trade - Second Edition, 2012

Introduction to the Special Section on Deep Learning for Speech and Language Processing.
IEEE Trans. Speech Audio Process., 2012

Acoustic Modeling Using Deep Belief Networks.
IEEE Trans. Speech Audio Process., 2012

An Efficient Learning Procedure for Deep Boltzmann Machines.
Neural Comput., 2012

Visualizing non-metric similarities in multiple maps.
Mach. Learn., 2012

Improving neural networks by preventing co-adaptation of feature detectors
CoRR, 2012

A Better Way to Pretrain Deep Boltzmann Machines.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Deep Lambertian Networks.
Proceedings of the 29th International Conference on Machine Learning, 2012

Deep Mixtures of Factor Analysers.
Proceedings of the 29th International Conference on Machine Learning, 2012

Learning to Label Aerial Images from Noisy Data.
Proceedings of the 29th International Conference on Machine Learning, 2012

Understanding how Deep Belief Networks perform acoustic modelling.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Robust Boltzmann Machines for recognition and denoising.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Discovering Binary Codes for Documents by Learning Deep Generative Models.
Top. Cogn. Sci., 2011

Two Distributed-State Models For Generating High-Dimensional Time Series.
J. Mach. Learn. Res., 2011

A better way to learn features: technical perspective.
Commun. ACM, 2011

Conditional Restricted Boltzmann Machines for Structured Output Prediction.
Proceedings of the UAI 2011, 2011

Generating Text with Recurrent Neural Networks.
Proceedings of the 28th International Conference on Machine Learning, 2011

Deep belief nets for natural language call-routing.
Proceedings of the IEEE International Conference on Acoustics, 2011

Deep Belief Networks using discriminative features for phone recognition.
Proceedings of the IEEE International Conference on Acoustics, 2011

Learning a better representation of speech soundwaves using restricted boltzmann machines.
Proceedings of the IEEE International Conference on Acoustics, 2011

Transforming Auto-Encoders.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Using very deep autoencoders for content-based image retrieval.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Modeling the joint density of two images under a variety of transformations.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

On deep generative models with applications to recognition.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Deep Belief Nets.
Proceedings of the Encyclopedia of Machine Learning, 2010

Boltzmann Machines.
Proceedings of the Encyclopedia of Machine Learning, 2010

Temporal-Kernel Recurrent Neural Networks.
Neural Networks, 2010

Comparing Classification Methods for Longitudinal fMRI Studies.
Neural Comput., 2010

Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines.
Neural Comput., 2010

Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Generating more realistic images using gated MRF's.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Gated Softmax Classification.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning to combine foveal glimpses with a third-order Boltzmann machine.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Binary coding of speech spectrograms using a deep auto-encoder.
Proceedings of the INTERSPEECH 2010, 2010

Rectified Linear Units Improve Restricted Boltzmann Machines.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Phone recognition using Restricted Boltzmann Machines.
Proceedings of the IEEE International Conference on Acoustics, 2010

Learning to Detect Roads in High-Resolution Aerial Images.
Proceedings of the Computer Vision - ECCV 2010, 2010

Dynamical binary latent variable models for 3D human pose tracking.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Modeling pixel means and covariances using factorized third-order boltzmann machines.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Deep belief networks.
Scholarpedia, 2009

Deep Boltzmann Machines.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Improving a statistical language model through non-linear prediction.
Neurocomputing, 2009

Semantic hashing.
Int. J. Approx. Reason., 2009

Products of Hidden Markov Models: It Takes N>1 to Tango.
Proceedings of the UAI 2009, 2009

Replicated Softmax: an Undirected Topic Model.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Zero-shot Learning with Semantic Output Codes.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

3D Object Recognition with Deep Belief Nets.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Workshop summary: Workshop on learning feature hierarchies.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Using fast weights to improve persistent contrastive divergence.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Factored conditional restricted Boltzmann Machines for modeling motion style.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Learning Generative Texture Models with extended Fields-of-Experts.
Proceedings of the British Machine Vision Conference, 2009

2008
Deep, Narrow Sigmoid Belief Networks Are Universal Approximators.
Neural Comput., 2008

The Recurrent Temporal Restricted Boltzmann Machine.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Using matrices to model symbolic relationship.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Generative versus discriminative training of RBMs for classification of fMRI images.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Implicit Mixtures of Restricted Boltzmann Machines.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

A Scalable Hierarchical Distributed Language Model.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Analysis-by-Synthesis by Learning to Invert Generative Black Boxes.
Proceedings of the Artificial Neural Networks, 2008

Improving a statistical language model by modulating the effects of context words.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007
Boltzmann machine.
Scholarpedia, 2007

Learning Multilevel Distributed Representations for High-Dimensional Sequences.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Visualizing Similarity Data with a Mixture of Maps.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Modeling image patches with a directed hierarchy of Markov random fields.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Restricted Boltzmann machines for collaborative filtering.
Proceedings of the Machine Learning, 2007

Three new graphical models for statistical language modelling.
Proceedings of the Machine Learning, 2007

Unsupervised Learning of Image Transformations.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006
Topographic Product Models Applied to Natural Scene Statistics.
Neural Comput., 2006

A Fast Learning Algorithm for Deep Belief Nets.
Neural Comput., 2006

Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation.
Cogn. Sci., 2006

Modeling Human Motion Using Binary Latent Variables.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005
Improving dimensionality reduction with spectral gradient descent.
Neural Networks, 2005

Inferring Motor Programs from Images of Handwritten Digits.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

What kind of graphical model is the brain?
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Learning Causally Linked Markov Random Fields.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

On Contrastive Divergence Learning.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Probabilistic sequential independent components analysis.
IEEE Trans. Neural Networks, 2004

Reinforcement Learning with Factored States and Actions.
J. Mach. Learn. Res., 2004

Exponential Family Harmoniums with an Application to Information Retrieval.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Multiple Relational Embedding.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Neighbourhood Components Analysis.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Distinguishing text from graphics in on-line handwritten ink.
Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition, 2004

2003
Energy-Based Models for Sparse Overcomplete Representations.
J. Mach. Learn. Res., 2003

Efficient Parametric Projection Pursuit Density Estimation.
Proceedings of the UAI '03, 2003

Wormholes Improve Contrastive Divergence.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Recognizing Handwritten Digits Using Hierarchical Products of Experts.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Classical and Bayesian Inference in Neuroimaging: Theory.
NeuroImage, 2002

Training Products of Experts by Minimizing Contrastive Divergence.
Neural Comput., 2002

Local Physical Models for Interactive Character Animation.
Comput. Graph. Forum, 2002

In Memory of Ray Reiter (1939-2002).
AI Mag., 2002

Self Supervised Boosting.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Learning Sparse Topographic Representations with Products of Student-t Distributions.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Stochastic Neighbor Embedding.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

A New Learning Algorithm for Mean Field Boltzmann Machines.
Proceedings of the Artificial Neural Networks, 2002

A Desktop Input Device and Interface for Interactive 3D Character Animation.
Proceedings of the Graphics Interface 2002 Conference, 2002

2001
Learning Distributed Representations of Concepts Using Linear Relational Embedding.
IEEE Trans. Knowl. Data Eng., 2001

Learning Distributed Representations of Relational Data using Linear Relational Embedding.
Proceedings of the 12th Italian Workshop on Neural Nets, 2001

Discovering Multiple Constraints that are Frequently Approximately Satisfied.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Global Coordination of Local Linear Models.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Learning Hierarchical Structures with Linear Relational Embedding.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Relative Density Nets: A New Way to Combine Backpropagation with HMM's.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Products of Hidden Markov Models.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates.
J. VLSI Signal Process., 2000

SMEM Algorithm for Mixture Models.
Neural Comput., 2000

Variational Learning for Switching State-Space Models.
Neural Comput., 2000

Rate-coded Restricted Boltzmann Machines for Face Recognition.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Recognizing Hand-written Digits Using Hierarchical Products of Experts.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Extracting Distributed Representations of Concepts and Relations from Positive and Negative Propositions.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Modeling High-Dimensional Data by Combining Simple Experts.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999
Variational Learning in Nonlinear Gaussian Belief Networks.
Neural Comput., 1999

Learning to Parse Images.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Spiking Boltzmann Machines.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998
Glove-TalkII-a neural-network interface which maps gestures to parallel formant speech synthesizer controls.
IEEE Trans. Neural Networks, 1998

Coaching variables for regression and classification.
Stat. Comput., 1998

NeuroAnimator: Fast Neural Network Emulation and Control of Physics-based Models.
Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, 1998

Fast Neural Network Emulation of Dynamical Systems for Computer Animation.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants.
Proceedings of the Learning in Graphical Models, 1998

A Hierarchical Community of Experts.
Proceedings of the Learning in Graphical Models, 1998

1997
Modeling the manifolds of images of handwritten digits.
IEEE Trans. Neural Networks, 1997

Glove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls.
IEEE Trans. Neural Networks, 1997

A Mobile Robot that Learns its Place.
Neural Comput., 1997

Using Expectation-Maximization for Reinforcement Learning.
Neural Comput., 1997

Instantiating Deformable Models with a Neural Net.
Comput. Vis. Image Underst., 1997

Efficient Stochastic Source Coding and an Application to a Bayesian Network Source Model.
Comput. J., 1997

Learning fast neural network emulators for physics-based models.
Proceedings of the ACM SIGGRAPH 97 Visual Proceedings: The art and interdisciplinary programs of SIGGRAPH '97, 1997

Hierarchical Non-linear Factor Analysis and Topographic Maps.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1996
Using Generative Models for Handwritten Digit Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., 1996

Varieties of Helmholtz Machine.
Neural Networks, 1996

Free Energy Coding.
Proceedings of the 6th Data Compression Conference (DCC '96), Snowbird, Utah, USA, March 31, 1996

1995
Learning Population Codes by Minimizing Description Length.
Neural Comput., 1995

The Helmholtz machine.
Neural Comput., 1995

Using Pairs of Data-Points to Define Splits for Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Does the Wake-sleep Algorithm Produce Good Density Estimators?
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

GloveTalkII: An Adaptive Gesture-to-Formant Interface.
Proceedings of the Human Factors in Computing Systems, 1995

1994
An Alternative Model for Mixtures of Experts.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Using a neural net to instantiate a deformable model.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Recognizing Handwritten Digits Using Mixtures of Linear Models.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993
Glove-Talk: a neural network interface between a data-glove and a speech synthesizer.
IEEE Trans. Neural Networks, 1993

A soft decision-directed LMS algorithm for blind equalization.
IEEE Trans. Commun., 1993

Learning Mixture Models of Spatial Coherence.
Neural Comput., 1993

Developing Population Codes by Minimizing Description Length.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Autoencoders, Minimum Description Length and Helmholtz Free Energy.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Keeping the Neural Networks Simple by Minimizing the Description Length of the Weights.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992
Simplifying Neural Networks by Soft Weight-Sharing.
Neural Comput., 1992

Feudal Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991
Adaptive Mixtures of Local Experts.
Neural Comput., 1991

Adaptive Soft Weight Tying using Gaussian Mixtures.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Adaptive Elastic Models for Hand-Printed Character Recognition.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Learning to Make Coherent Predictions in Domains with Discontinuities.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990
A time-delay neural network architecture for isolated word recognition.
Neural Networks, 1990

The Bootstrap Widrow-Hoff Rule as a Cluster-Formation Algorithm.
Neural Comput., 1990

Mapping Part-Whole Hierarchies into Connectionist Networks.
Artif. Intell., 1990

Connectionist Symbol Processing - Preface.
Artif. Intell., 1990

Discovering Viewpoint-Invariant Relationships That Characterize Objects.
Proceedings of the Advances in Neural Information Processing Systems 3, 1990

Evaluation of Adaptive Mixtures of Competing Experts.
Proceedings of the Advances in Neural Information Processing Systems 3, 1990

Building adaptive interfaces with neural networks: The glove-talk pilot study.
Proceedings of the Human-Computer Interaction, 1990

Distributed Representations.
Proceedings of the Philosophy of Artificial Intelligence., 1990

1989
Phoneme recognition using time-delay neural networks.
IEEE Trans. Acoust. Speech Signal Process., 1989

Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space.
Neural Comput., 1989

Connectionist Learning Procedures.
Artif. Intell., 1989

TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations.
Proceedings of the Advances in Neural Information Processing Systems 2, 1989

Dimensionality Reduction and Prior Knowledge in E-Set Recognition.
Proceedings of the Advances in Neural Information Processing Systems 2, 1989

Discovering High Order Features with Mean Field Modules.
Proceedings of the Advances in Neural Information Processing Systems 2, 1989

1988
A Distributed Connectionist Production System.
Cogn. Sci., 1988

GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection.
Proceedings of the Advances in Neural Information Processing Systems 1, 1988

Phoneme recognition: neural networks vs. hidden Markov models.
Proceedings of the IEEE International Conference on Acoustics, 1988

1987
Connectionist Architectures for Artificial Intelligence.
Computer, 1987

How Learning Can Guide Evolution.
Complex Syst., 1987

Learning Translation Invariant Recognition in Massively Parallel Networks.
Proceedings of the PARLE, 1987

Learning Representations by Recirculation.
Proceedings of the Neural Information Processing Systems, Denver, Colorado, USA, 1987, 1987

1986
Learning in Massively Parallel Nets (Panel).
Proceedings of the 5th National Conference on Artificial Intelligence. Philadelphia, 1986

1985
A Learning Algorithm for Boltzmann Machines.
Cogn. Sci., 1985

Symbols Among the Neurons: Details of a Connectionist Inference Architecture.
Proceedings of the 9th International Joint Conference on Artificial Intelligence. Los Angeles, 1985

Shape Recognition and Illusory Conjunctions.
Proceedings of the 9th International Joint Conference on Artificial Intelligence. Los Angeles, 1985

1983
Massively Parallel Architectures for AI: NETL, Thistle, and Boltzmann Machines.
Proceedings of the National Conference on Artificial Intelligence, 1983

1981
A Parallel Computation that Assigns Canonical Object-Based Frames of Reference.
Proceedings of the 7th International Joint Conference on Artificial Intelligence, 1981

Shape Representation in Parallel Systems.
Proceedings of the 7th International Joint Conference on Artificial Intelligence, 1981

1979
Some Demonstrations of the Effects of Structural Descriptions in Mental Imagery.
Cogn. Sci., 1979

1978
Representation and Control in Vision.
Proceedings of AISB/GI Conference (Proceedings of the 4th European Conference on Artificial Intelligence), 1978

1977
Relaxation and its role in vision.
PhD thesis, 1977

1976
Using Relaxation to find a Puppet.
Proceedings of the Summer Conference on Artificial Intelligence and Simulation of Behaviour, Edinburgh, UK, 12th, 1976


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