Geoffrey Hinton

Q: What Schools Are Affiliated With Geoffrey Hinton

Geoffrey Hinton is affiliated with the following schools: University of Western Ontario, Carnegie Mellon University, University of Edinburgh, University of Toronto

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Why Is Geoffrey Hinton Influential?

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According to Wikipedia, Geoffrey Everest Hinton is a British-Canadian cognitive psychologist and computer scientist, most noted for his work on artificial neural networks. From 2013 to 2023, he divided his time working for Google and the University of Toronto, before publicly announcing his departure from Google in May 2023, citing concerns about the risks of artificial intelligence technology. In 2017, he co-founded and became the chief scientific advisor of the Vector Institute in Toronto.

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Geoffrey Hinton's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

ImageNet classification with deep convolutional neural networks (2012) (96741)
Deep Learning (2015) (62354)
Dropout: a simple way to prevent neural networks from overfitting (2014) (32886)
Visualizing Data using t-SNE (2008) (28307)
Learning representations by back-propagating errors (1986) (22496)
Learning internal representations by error propagation (1986) (20156)
Reducing the Dimensionality of Data with Neural Networks (2006) (16584)
Rectified Linear Units Improve Restricted Boltzmann Machines (2010) (15007)
A Fast Learning Algorithm for Deep Belief Nets (2006) (14699)
Distilling the Knowledge in a Neural Network (2015) (11818)
A Simple Framework for Contrastive Learning of Visual Representations (2020) (8450)
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups (2012) (8149)
Speech recognition with deep recurrent neural networks (2013) (7650)
Improving neural networks by preventing co-adaptation of feature detectors (2012) (6887)
Training Products of Experts by Minimizing Contrastive Divergence (2002) (4936)
Layer Normalization (2016) (4364)
Adaptive Mixtures of Local Experts (1991) (4293)
On the importance of initialization and momentum in deep learning (2013) (4081)
A Learning Algorithm for Boltzmann Machines (1985) (3699)
Dynamic Routing Between Capsules (2017) (3517)
A Practical Guide to Training Restricted Boltzmann Machines (2012) (2955)
Phoneme recognition using time-delay neural networks (1989) (2923)
A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants (1998) (2700)
Deep Neural Networks for Acoustic Modeling in Speech Recognition (2012) (2360)
Deep Boltzmann Machines (2009) (2194)
Restricted Boltzmann machines for collaborative filtering (2007) (1967)
Neighbourhood Components Analysis (2004) (1821)
Acoustic Modeling Using Deep Belief Networks (2012) (1750)
Connectionist Learning Procedures (1989) (1653)
Stochastic Neighbor Embedding (2002) (1641)
Learning representations by back-propagation errors, nature (1986) (1402)
Learning and relearning in Boltzmann machines (1986) (1377)
Generating Text with Recurrent Neural Networks (2011) (1375)
Semantic hashing (2009) (1335)
Big Self-Supervised Models are Strong Semi-Supervised Learners (2020) (1319)
Improving deep neural networks for LVCSR using rectified linear units and dropout (2013) (1306)
Distributed Representations (1986) (1292)
Unsupervised Learning (1999) (1283)
The Helmholtz Machine (1995) (1247)
How Learning Can Guide Evolution (1996) (1208)
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer (2017) (1149)
Autoencoders, Minimum Description Length and Helmholtz Free Energy (1993) (1129)
The "wake-sleep" algorithm for unsupervised neural networks. (1995) (1057)
When Does Label Smoothing Help? (2019) (1050)
Keeping the neural networks simple by minimizing the description length of the weights (1993) (1048)
New types of deep neural network learning for speech recognition and related applications: an overview (2013) (1011)
A Scalable Hierarchical Distributed Language Model (2008) (985)
Learning multiple layers of representation (2007) (976)
Transforming Auto-Encoders (2011) (965)
Learning distributed representations of concepts. (1989) (945)
Zero-shot Learning with Semantic Output Codes (2009) (929)
Grammar as a Foreign Language (2014) (884)
Regularizing Neural Networks by Penalizing Confident Output Distributions (2017) (871)
A general framework for parallel distributed processing (1986) (868)
Parallel Models of Associative Memory (1989) (868)
Matrix capsules with EM routing (2018) (856)
Schemata and Sequential Thought Processes in PDP Models (1986) (814)
On Contrastive Divergence Learning (2005) (764)
The EM algorithm for mixtures of factor analyzers (1996) (744)
Feudal Reinforcement Learning (1992) (710)
Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems (1991) (708)
Simplifying Neural Networks by Soft Weight-Sharing (1992) (691)
A time-delay neural network architecture for isolated word recognition (1990) (661)
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units (2015) (634)
Three new graphical models for statistical language modelling (2007) (632)
Modeling Human Motion Using Binary Latent Variables (2006) (625)
Similarity of Neural Network Representations Revisited (2019) (623)
Parameter estimation for linear dynamical systems (1996) (605)
The appeal of parallel distributed processing (1986) (604)
OPTIMAL PERCEPTUAL INFERENCE (1983) (576)
Learning representations of back-propagation errors (1986) (556)
Replicated Softmax: an Undirected Topic Model (2009) (539)
Learning to Detect Roads in High-Resolution Aerial Images (2010) (536)
On rectified linear units for speech processing (2013) (516)
Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure (2007) (515)
Exponential Family Harmoniums with an Application to Information Retrieval (2004) (513)
Lookahead Optimizer: k steps forward, 1 step back (2019) (507)
How neural networks learn from experience. (1992) (482)
Machine Learning for Aerial Image Labeling (2013) (480)
Distilling a Neural Network Into a Soft Decision Tree (2017) (477)
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models (2016) (456)
Self-organizing neural network that discovers surfaces in random-dot stereograms (1992) (455)
SMEM Algorithm for Mixture Models (1998) (455)
Deep Belief Networks for phone recognition (2009) (445)
Glove-Talk: a neural network interface between a data-glove and a speech synthesizer (1993) (439)
Lesioning an attractor network: investigations of acquired dyslexia (1991) (438)
An Efficient Learning Procedure for Deep Boltzmann Machines (2012) (434)
Modeling the manifolds of images of handwritten digits (1997) (426)
Deep belief networks (2009) (426)
The Recurrent Temporal Restricted Boltzmann Machine (2008) (415)
Application of Deep Belief Networks for Natural Language Understanding (2014) (414)
Factored conditional restricted Boltzmann Machines for modeling motion style (2009) (413)
Learning to combine foveal glimpses with a third-order Boltzmann machine (2010) (409)
Using very deep autoencoders for content-based image retrieval (2011) (405)
Variational Learning for Switching State-Space Models (2000) (403)
Backpropagation and the brain (2020) (403)
Deep Learning-A Technology With the Potential to Transform Health Care. (2018) (402)
Experiments on Learning by Back Propagation. (1986) (398)
Learning to Label Aerial Images from Noisy Data (2012) (376)
Mapping Part-Whole Hierarchies into Connectionist Networks (1990) (375)
3D Object Recognition with Deep Belief Nets (2009) (370)
Binary coding of speech spectrograms using a deep auto-encoder (2010) (363)
NeuroAnimator: fast neural network emulation and control of physics-based models (1998) (352)
Parallel visual computation (1983) (346)
Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine (2010) (331)
A Distributed Connectionist Production System (1988) (329)
Deep Belief Networks using discriminative features for phone recognition (2011) (317)
To recognize shapes, first learn to generate images. (2007) (315)
Lesioning an attractor network: investigations of acquired dyslexia. (1991) (313)
Understanding how Deep Belief Networks perform acoustic modelling (2012) (311)
Using fast weights to improve persistent contrastive divergence (2009) (309)
Reducing the Dimensionality of Data with Neural (2008) (300)
Large scale distributed neural network training through online distillation (2018) (300)
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines (2010) (284)
Training Recurrent Neural Networks (2013) (281)
An Alternative Model for Mixtures of Experts (1994) (278)
Learning Generative Texture Models with extended Fields-of-Experts (2009) (274)
Generative models for discovering sparse distributed representations. (1997) (265)
Modeling pixel means and covariances using factorized third-order boltzmann machines (2010) (263)
Learning Multilevel Distributed Representations for High-Dimensional Sequences (2007) (247)
Global Coordination of Local Linear Models (2001) (246)
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images (2010) (245)
Visualizing non-metric similarities in multiple maps (2011) (239)
Proceedings of the 1988 Connectionist Models Summer School (1989) (238)
Using fast weights to deblur old memories (1987) (235)
Transforming Autoencoders (2011) (229)
Some Demonstrations of the Effects of Structural Descriptions in Mental Imagery (1979) (226)
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes (2007) (225)
Massively Parallel Architectures for AI: NETL, Thistle, and Boltzmann Machines (1983) (223)
On deep generative models with applications to recognition (2011) (221)
Unsupervised Learning of Image Transformations (2007) (221)
Deep learning for AI (2021) (220)
A Parallel Computation that Assigns Canonical Object-Based Frames of Reference (1981) (219)
Learning a better representation of speech soundwaves using restricted boltzmann machines (2011) (218)
Learning Translation Invariant Recognition in Massively Parallel Networks (1987) (214)
Using Generative Models for Handwritten Digit Recognition (1996) (207)
Symbols Among the Neurons: Details of a Connectionist Inference Architecture (1985) (207)
Stacked Capsule Autoencoders (2019) (206)
Using Expectation-Maximization for Reinforcement Learning (1997) (199)
Distributed representations and nested compositional structure (1994) (199)
Using Fast Weights to Attend to the Recent Past (2016) (188)
Neural Additive Models: Interpretable Machine Learning with Neural Nets (2020) (186)
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures (2018) (185)
Energy-Based Models for Sparse Overcomplete Representations (2003) (185)
Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space (1989) (184)
Unsupervised learning : foundations of neural computation (1999) (179)
Phoneme recognition: neural networks vs. hidden Markov models vs. hidden Markov models (1988) (176)
CvxNet: Learnable Convex Decomposition (2019) (173)
THE EFFECTS OF METHYLPHENIDATE (RITALIN) ON THE MOTOR SKILLS AND BEHAVIOR OF CHILDREN WITH LEARNING PROBLEMS (1969) (171)
Robust Boltzmann Machines for recognition and denoising (2012) (170)
Who Said What: Modeling Individual Labelers Improves Classification (2017) (170)
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition-' Washington , D . C . , June , 1983 OPTIMAL PERCEPTUAL INFERENCE (2011) (169)
Products of experts (1999) (167)
Rate-coded Restricted Boltzmann Machines for Face Recognition (2000) (165)
Reinforcement Learning with Factored States and Actions (2004) (159)
Learning Representations by Recirculation (1987) (158)
Dynamical binary latent variable models for 3D human pose tracking (2010) (158)
Learning Sparse Topographic Representations with Products of Student-t Distributions (2002) (156)
Parallel computations for controlling an arm. (1984) (154)
20 – CONNECTIONIST LEARNING PROCEDURES1 (1990) (154)
Deep, Narrow Sigmoid Belief Networks Are Universal Approximators (2008) (149)
Glove-TalkII-a neural-network interface which maps gestures to parallel formant speech synthesizer controls (1997) (148)
Connectionist Architectures for Artificial Intelligence (1990) (146)
A New Learning Algorithm for Mean Field Boltzmann Machines (2002) (143)
Modeling image patches with a directed hierarchy of Markov random fields (2007) (142)
Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation (2006) (137)
Deep belief nets for natural language call-routing (2011) (136)
Preface to the Special Issue on Connectionist Symbol Processing (1990) (135)
Varieties of Helmholtz Machine (1996) (134)
Learning sets of filters using back-propagation (1987) (131)
Recognizing Handwritten Digits Using Mixtures of Linear Models (1994) (130)
A Better Way to Pretrain Deep Boltzmann Machines (2012) (128)
Acoustic and surface EMG diagnosis of pediatric muscle disease (1990) (128)
Hyperpipecolatemia: A new metabolic disorder associated with neuropathy and hepatomegaly: A case study. (1968) (126)
Topographic Product Models Applied to Natural Scene Statistics (2006) (126)
Adaptive Elastic Models for Hand-Printed Character Recognition (1991) (124)
Modeling Documents with Deep Boltzmann Machines (2013) (124)
Learning Distributed Representations of Concepts Using Linear Relational Embedding (2001) (123)
Two Distributed-State Models For Generating High-Dimensional Time Series (2011) (122)
Separating Figure from Ground with a Parallel Network (1986) (122)
Conditional Restricted Boltzmann Machines for Structured Output Prediction (2011) (122)
Phone recognition using Restricted Boltzmann Machines (2010) (118)
The shared views of four research groups ) (2012) (114)
Discovering Binary Codes for Documents by Learning Deep Generative Models (2011) (113)
Evaluation of Adaptive Mixtures of Competing Experts (1990) (113)
Modeling documents with a Deep Boltzmann Machine (2013) (113)
Scene-based and viewer-centered representations for comparing shapes (1988) (111)
Learning symmetry groups with hidden units: beyond the perceptron (1986) (109)
Shape Representation in Parallel Systems (1981) (108)
Generating Facial Expressions with Deep Belief Nets (2008) (104)
Gated Softmax Classification (2010) (103)
Visualizing Similarity Data with a Mixture of Maps (2007) (102)
How to Represent Part-Whole Hierarchies in a Neural Network (2021) (98)
Learning to represent visual input (2010) (97)
Switching State-Space Models (1996) (95)
A comparison of statistical learning methods on the Gusto database. (1998) (91)
Implicit Mixtures of Restricted Boltzmann Machines (2008) (90)
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss (2019) (89)
Simulating brain damage. (1993) (89)
Imputer: Sequence Modelling via Imputation and Dynamic Programming (2020) (87)
Learning and Applying Contextual Constraints in Sentence Comprehension (1991) (86)
A Mobile Robot That Learns Its Place (1997) (85)
Generative versus discriminative training of RBMs for classification of fMRI images (2008) (83)
Deep Lambertian Networks (2012) (83)
Variational Learning in Nonlinear Gaussian Belief Networks (1999) (83)
Recognizing Hand-written Digits Using Hierarchical Products of Experts (2002) (83)
Relaxation and its role in vision (1977) (83)
Deep Learning in Natural Language Processing (2018) (82)
Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates (1998) (81)
Generating more realistic images using gated MRF's (2010) (80)
The delve manual (1996) (79)
Mental simulation (1990) (78)
Introduction to the Special Section on Deep Learning for Speech and Language Processing (2012) (77)
Where Do Features Come From? (2014) (77)
A Desktop Input Device and Interface for Interactive 3D Character Animation (2002) (76)
Learning Sparse Networks Using Targeted Dropout (2019) (74)
Shape Recognition and Illusory Conjunctions (1985) (74)
Rectiﬁed Linear Units Improve Restricted Boltzmann Machines (72)
A soft decision-directed LMS algorithm for blind equalization (1993) (71)
Deep Mixtures of Factor Analysers (2012) (69)
Glove-TalkII: an adaptive gesture-to-formant interface (1995) (67)
Does the Wake-sleep Algorithm Produce Good Density Estimators? (1995) (63)
GTM through time (1997) (62)
Modeling the joint density of two images under a variety of transformations (2011) (61)
Learning to Parse Images (1999) (61)
Glove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls (1997) (61)
Separating figure from ground with a Boltzmann machine (1990) (59)
Tensor Analyzers (2013) (59)
Building adaptive interfaces with neural networks: The glove-talk pilot study (1990) (58)
Modeling Natural Images Using Gated MRFs (2013) (58)
What kind of graphical model is the brain? (2005) (58)
Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks (1994) (57)
G-maximization: An unsupervised learning procedure for discovering regularities (1987) (57)
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions (2019) (56)
Cerebellar astrocytoma with benign histology and malignant clinical course. Case report. (1981) (56)
A variant form of metachromatic leukodystrophy without arylsulfatase deficiency (1982) (55)
Learning Mixture Models of Spatial Coherence (1993) (55)
Keeping Neural Networks Simple (1993) (53)
Self Supervised Boosting (2002) (50)
Inferring Motor Programs from Images of Handwritten Digits (2005) (50)
Mean field networks that learn to discriminate temporally distorted strings (1991) (50)
A Hierarchical Community of Experts (1999) (48)
Implementing Semantic Networks in Parallel Hardware (2014) (48)
Mundane Reasoning by Parallel Constraint Satisfaction (1990) (47)
Learning Population Codes by Minimizing Description Length (1993) (47)
Temporal-Kernel Recurrent Neural Networks (2010) (46)
The Bootstrap Widrow-Hoff Rule as a Cluster-Formation Algorithm (1990) (46)
Multiple Relational Embedding (2004) (46)
Comparing Classification Methods for Longitudinal fMRI Studies (2010) (46)
Deep Belief Nets (2017) (45)
Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search (2018) (44)
Analysis-by-Synthesis by Learning to Invert Generative Black Boxes (2008) (43)
Bayesian networks for pattern classification, data compression, and channel coding (1997) (42)
Spiking Boltzmann Machines (1999) (41)
Untimed and Misrepresented: Connectionism and the Computer Metaphor Untimed and Misrepresented: Connectionism and the Computer Metaphor (1992) (41)
DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules (2018) (41)
Dimensionality Reduction and Prior Knowledge in E-Set Recognition (1989) (40)
Discovering Viewpoint-Invariant Relationships That Characterize Objects (1990) (39)
Local Physical Models for Interactive Character Animation (2002) (38)
Products of Hidden Markov Models (2001) (38)
Connectionist Symbol Processing (1991) (38)
Reinforcement learning for factored Markov decision processes (2002) (36)
Learning Causally Linked Markov Random Fields (2005) (35)
Adaptive Soft Weight Tying using Gaussian Mixtures (1991) (35)
Hierarchical Non-linear Factor Analysis and Topographic Maps (1997) (34)
Developing Population Codes by Minimizing Description Length (1993) (34)
Successful Treatment of Hereditary Trembling Chin With Botulinum Toxin (1993) (31)
Discovering Multiple Constraints that are Frequently Approximately Satisfied (2001) (31)
Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task (2000) (30)
Using EM for Reinforcement Learning (2000) (29)
Unsupervised part representation by Flow Capsules (2020) (28)
A Mode-Hopping MCMC sampler (2003) (28)
Guest Editorial: Deep Learning (2015) (26)
GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection (1988) (26)
Using matrices to model symbolic relationship (2008) (24)
Boltzmann machine (2007) (24)
TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations (1989) (23)
Efficient Stochastic Source Coding and an Application to a Bayesian Network Source Model (1997) (23)
A New View of ICA (2001) (22)
Learning Hierarchical Structures with Linear Relational Embedding (2001) (22)
The ups and downs of Hebb synapses. (2003) (22)
Improving a statistical language model through non-linear prediction (2009) (21)
Coaching variables for regression and classification (1998) (21)
BoltzCONS: Dynamic Symbol Structures in a Connectionist Network (1991) (21)
Using Relaxation to find a Puppet (1976) (21)
A simple algorithm that discovers efficient perceptual codes (1997) (21)
Combining deformable models and neural networks for handprinted digit recognition (1994) (20)
Spatial coherence as an internal teacher for a neural network (1995) (19)
Using an autoencoder with deformable templates to discover features for automated speech recognition (2013) (19)
Subclass Distillation (2020) (19)
Children with Learning Problems: Academic History, Academic Prediction, and Adjustment Three Years After Assessment (1971) (19)
Deterministic Boltzmann Learning in Networks with Asymmetric Connectivity (1991) (19)
Autoregressive product of multi-frame predictions can improve the accuracy of hybrid models (2014) (19)
Canonical Capsules: Unsupervised Capsules in Canonical Pose (2020) (19)
Teaching with Commentaries (2020) (19)
Extracting distributed representations of concepts and relations from positive and negative propositions (2000) (18)
Free energy coding (1996) (18)
Wormholes Improve Contrastive Divergence (2003) (17)
Using Pairs of Data-Points to Define Splits for Decision Trees (1995) (16)
Instantiating Deformable Models with a Neural Net (1997) (16)
A better way to learn features (2011) (16)
A Practical Guide to Training (2010) (16)
“Dark Knowledge” (2020) (16)
Why the Islands Move (1984) (15)
Improving dimensionality reduction with spectral gradient descent (2005) (15)
Deflecting Adversarial Attacks (2019) (15)
Checklist for Diagnosis of Brain Death (1991) (14)
Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine (2009) (14)
Tay-Sachs disease: B1 variant. (1988) (14)
Imagery without arrays (1979) (13)
Probabilistic sequential independent components analysis (2004) (13)
Hand-printed digit recognition using deformable models (1994) (13)
A new way to learn acoustic events (2011) (13)
Chapter IVb Some Computational Solutions to Bernstein's Problems (1984) (12)
Minimizing Description Length in an Unsupervised Neural Network (2000) (12)
Computation by neural networks (2000) (12)
Bethe free energy and contrastive divergence approximations for undirected graphical models (2003) (11)
Childhood Psychosis or Mental Retardation: A Diagnostic Dilemma. (1964) (11)
Dual Control (2010) (10)
Speech recognition using time‐delay neural networks (1988) (10)
Learning in parallel networks: simulating learning in a probabilistic system (1985) (10)
Using a neural net to instantiate a deformable model (1994) (9)
Fast Neural Network Emulation of Dynamical Systems for Computer Animation (1998) (9)
Discovering High Order Features with Mean Field Modules (1989) (9)
Minimal Brain Dysfunction: Clinical and Psychological Test Characteristics (1969) (9)
Aspartylglucosaminuria in a Canadian family. (1998) (8)
Representation and Control in Vision (1978) (8)
An Efficient Learning Procedure for Deep (2010) (8)
Products of Hidden Markov Models: It Takes N>1 to Tango (2009) (8)
Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space (2000) (7)
Intradural spinal hematoma in an infant with cystic fibrosis. (1986) (7)
Redes neuronales que aprenden de la experiencia (1992) (7)
Modeling High-Dimensional Data by Combining Simple Experts (2000) (7)
Combining two methods of recognizing hand-printed digits (1992) (7)
Heme‐Derived Bilins (2019) (7)
Inferring the meaning of direct perception (1980) (7)
LEARNING SEMANTIC FEATURES (1984) (7)
Learning in massively parallel nets (1986) (7)
Machine learning for neuroscience (2011) (7)
Training Products of Experts by Maximizing Contrastive Likelihood (1999) (6)
Efficient Parametric Projection Pursuit Density Estimation (2002) (6)
Bone mineral density and computer tomographic measurements in correlation with failure strength of equine metacarpal bones (2014) (6)
The AB-variant of metachromatic leukodystrophy (Postulated activator protein deficiency) (1981) (6)
Une nouvelle approche de la cognition : le connexionnisme (1987) (6)
Using Mixtures of Factor Analyzers for Segmentation and Pose Estimation (1997) (5)
Neural network architectures for artificial intelligence (1988) (5)
Unsupervised Learning: Foundations of Neural Computation--A Review (2001) (5)
Cerberus: A Multi-headed Derenderer (2019) (5)
Learnable Convex Decomposition (2020) (5)
How to generate realistic images using gated MRF ’ s (2010) (5)
Postnatal organic causes of mental retardation. (1962) (5)
The Horizontal—Vertical Delusion (1987) (5)
Automated motif discovery in protein structure prediction (1997) (5)
Ultrastructure and peroxidase of leucocytes in five patients with juvenile form of ceroid lipofuscinoses. (1976) (5)
The effect of hypothalamic lesions on growth. (1962) (5)
Learning Distributed Representations of Relational Data using Linear Relational Embedding (2001) (5)
The Next Generation of Neural Networks (2020) (5)
TRAINING MANY SMALL HIDDEN MARKOV MODELS (2001) (4)
Decision Stump (2010) (4)
Artificial Intelligence: Neural Networks (2005) (4)
Learning to Make Coherent Predictions in Domains with Discontinuities (1991) (4)
Relative Density Nets: A New Way to Combine Backpropagation with HMM's (2001) (3)
Number 20 (1998) (3)
Turn that frown upside-down! Inferring facial actions from pairs of images in a neurally plausible computational model (2010) (3)
ATRIX CAPSULES WITH EM ROUTING (2018) (3)
Improving a statistical language model by modulating the effects of context words (2008) (3)
Connectionist Models: Proceedings of the Summer School Held in San Diego, California on 1990 (1990) (3)
CHILDHOOD PSYCHOSIS OR MENTAL RETARDATION: A DIAGNOSTIC DILEMMA. II. PEDIATRIC AND NEUROLOGICAL ASPECTS. (1963) (3)
The Behaviorial Significance of Differing EEG Abnormalities in Children With Learning and/or Behavior Problems (1970) (3)
Connectionist Symbol Processing - Preface (1990) (2)
Workshop summary: Workshop on learning feature hierarchies (2009) (2)
Non-linear dimensionality reduction using neural networks (2006) (2)
DIGITAL MARIONETTE: augmenting kinematics with physics for multi-track desktop performance animation (2002) (2)
Cascaded redundancy reduction. (1998) (2)
Bias Variance Decomposition (2010) (2)
Task and Object Learning in Visual Recognition (1991) (2)
Developing a Mind: Learning in Humans, Animals, and Machines (2020) (2)
Fast Inference and Learning for Modeling Documents with a Deep Boltzmann Machine (2013) (2)
Scaling in a hierarchical unsupervised network (1999) (2)
Learning in Massively Parallel Nets (Panel) (1986) (1)
Learning fast neural network emulators for physics-based models (1997) (1)
Models of human inference (1987) (1)
is achieved. Prior to stabilization, neural networks do not jump around between points in activation space. Stabiliza-tion is the process whereby a network first generates a de-terminate activation pattern, and thereby arrives at a point in activation space (2004) (1)
The Development of the Time-Delayed Neural Network Architecture (1990) (1)
Pattern classification using a mixture of factor analyzers (1999) (1)
Approximate Contrastive Free Energies for Learning in Undirected Graphical Models (2001) (1)
Unsupervised Object Discovery via Capsule Decoders (2019) (1)
Atypical severe muscular dystrophy in a male: genetic implications for female relatives. (1985) (1)
COOPERATIVE : COMPUTATION (1)
Developing Population Codes For Object Instantiation Parameters (2001) (1)
Cascaded redundancy reduction (1998) (1)
0 Speeding up Backpropagation Algorithms (1997) (1)
Learning Pigeon Behaviour Using Binary Latent Variables (2009) (1)
Bellman Equation (2010) (1)
Paralysis after oral poliomyelitis vaccine. (1962) (1)
Intrauterine growth retardation and its impact on the neurological status of the newborn (1981) (1)
Recursive Distributed Representations (1991) (1)
Learning and Evaluaing Deep Bolztmann Machines (2009) (1)
Reviews: A Primer of Infant Development, Systems Neuroscience (1978) (1)
Using neural networks to learn intractable generative models (1994) (1)
Mundane Reasoning by Settling on a Plausible Model (1991) (1)
LEARNING IN BOLTZMANN MACHINES ' APPRENTISSAGE DANS LES MACHINES DE BOLTZMANN (1985) (1)
Three frames suffice (1985) (1)
Using matrices to model symbolic relationships (2008) (1)
Simulating Brain Damage Adults with brain damage make some bizarre errors when reading words . If a network of simulated neurons is trained to read and then is damaged , it produces strikingly similar behavior (1999) (0)
A Bayesian Unsupervised Learning Algorithm that Scales (2007) (0)
learning can then be used to fine-tune the CD solution . 1 ON CONTRASTIVE DIVERGENCE LEARNING (1998) (0)
Système et méthode de résolution du problème de surapprentissage dans un réseau de neurones (2013) (0)
R M R S E N T a T I O N and Control in Vision ($5 ) (2012) (0)
Detergent compositions containing percarbonate (1998) (0)
Inverting Generative Black Boxes with Breeder Learning (2006) (0)
認知・学習のコネクショニストモデル (機械は考えるか ) (1987) (0)
Multifacility Location Problem using Scaled Conjugate Gradient Algorithm under Triangular Area Constraints (2017) (0)
Boltzmann Machines (2010) (0)
Performance analysis of Neural Network Classifier for the Different Number of Hidden Units (2014) (0)
Awards and Distinguished Papers (2011) (0)
Who’s Who in the Zoo: Defining Roles and Responsibilities of a Collaborative Health Care Team Abstract (2018) (0)
Modeling Semantic Similarities in Multiple Maps (2009) (0)
Cerberus : A Multiheaded Derenderer (2019) (0)
Preventive psychotherapeutic measures for use with non-vocal clients. A case study. (1982) (0)
Detecting Handwritten Text from Forms using Deep Learning (2020) (0)
The way things ought to be (2003) (0)
Learning spatially coherent properties of the visual world in connectionist networks (1991) (0)
APPRENTISSAGE DANS LES MACHINES DE BOLTZMANN (1986) (0)
nerative Models for andwritten Digit Recognition (1996) (0)
Thanks to our guest reviewers (1985) (0)
Bias toward Higher Performance for the Decomposed Network. Whether a Decomposed Network Would Learn (1991) (0)
Simulación de lesiones cerebrales (1993) (0)
7. Conclusion and Future Work Novel Objective Function for Improved Phoneme Recognition Using Time-delay Neural Networks. 5. Simulation Results (0)
Report from Dagstuhl Seminar 14381 Neural-Symbolic Learning and Reasoning (2015) (0)
Système et procédé permettant de paralléliser des réseaux neuronaux classiques (2013) (0)
Fast Neural Network Emulation and Control of Dynamical Systems (1999) (0)
In Memory of Ray Reiter (1939-2002) (2002) (0)
November 21 , 2000 GCNU TR 2000 – 008 Products of Hidden Markov Models (2001) (0)
CSC 2535 2011 ASSIGNMENT 2 (2011) (0)
Maximizing Mutual Information (0)
Networks Reducing the Dimensionality of Data with Neural (2008) (0)
Sustainability Attitudes of College Students as Future Business Leaders (2018) (0)
Recluse Oil Field (1968) (0)
The assessment and management of recurrent headaches in children (1987) (0)
JUVENILE FORM OF CEROID LIPOFUSCINOSES (1976) (0)
NEUROMUSCULAR: ACOUSTIC AND SURFACE EMG DIAGNOSIS OF PEDIATRIC MUSCLE DISEASE (1990) (0)
Who Said What: Modelling Individual Labels Improves Classification (2017) (0)
A Neurodegenerative Disorder in a 10 Year Old Boy (1987) (0)
Proceedings of the Connectionists Models Summer School Held in Pittsburgh, Pennsylvania on June 17-26, 1988 (1989) (0)
Developing Population Codes For (1993) (0)
Proceedings of the 1990 Summer School on Connectionist models (1991) (0)
Artificial Intelligence, Linguistics, Neuroscience, Philosophy, Psychology (1996) (0)
Scaling in a Hierarchical Unsupervised Network 1 (2000) (0)
Scalingin a Hierar chical UnsupervisedNetwork (1999) (0)
Activity in Cognitive Elements 48 (1991) (0)
Guest Editorial: Deep Learning (2015) (0)
Shape Rfprfsfntatton in Parallel Systems (0)
Embedding viaclustering: Using spectral information toguidedimensionality reduction (2005) (0)
P IX 2 SEQ : A L ANGUAGE M ODELING F RAMEWORK FOR O BJECT D ETECTION (2022) (0)
Artificial Intelligence Cytometer in Blood (2019) (0)
198 1 Iters in the Brain (0)
23 Generating Facial Expressions with Deep Belief Nets (2008) (0)

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