← Authors

Geoffrey E. Hinton

32 papers · 2003–2022 · 3 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer πŸƒ Academic Marathon (19) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (3) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (30) 🏠 Conference Loyalist (28) 🌟 Keyword Trendsetter Combo (6) πŸ† Keyword Champion πŸ”¬ Deep Specialist (16) 🌱 Topic Pioneer πŸ—ƒοΈ Keyword Collector (114) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner πŸ’Ž Century Club (32) πŸ”₯ Unstoppable (7)

Conferences

NIPS (28) JMLR (3) ICLR (1)

Top co-authors

Graham W. Taylor (3) Ilya Sutskever (3) Ruslan Salakhutdinov (3) Sara Sabour (3) Vinod Nair (2) Simon Kornblith (2) Jimmy Ba (2) Sam T. Roweis (2) Volodymyr Mnih (2) Ting Chen (2)

Keywords

generative model (11) neural network (8) restricted boltzmann machine (5) deep belief network (5) image classification (4) latent variable (3) capsule network (3) convolutional neural network (3) motion capture (3) deep belief net (3) object recognition (3) unsupervised learning (3) attention mechanism (3) markov random field (2) probabilistic model (2) feature learning (2) boltzmann machine (2) latent variable model (2) semi-supervised learning (2) knowledge distillation (2)

Papers

A Unified Sequence Interface for Vision Tasks NIPS 2022
Canonical Capsules: Self-Supervised Capsules in Canonical Pose NIPS 2021
Neural Additive Models: Interpretable Machine Learning with Neural Nets NIPS 2021
Big Self-Supervised Models are Strong Semi-Supervised Learners NIPS 2020
Lookahead Optimizer: k steps forward, 1 step back NIPS 2019
When does label smoothing help? NIPS 2019
Stacked Capsule Autoencoders NIPS 2019
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures NIPS 2018
Large scale distributed neural network training through online distillation ICLR 2018
Dynamic Routing Between Capsules NIPS 2017
Using Fast Weights to Attend to the Recent Past NIPS 2016
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models NIPS 2016
ImageNet Classification with Deep Convolutional Neural Networks NIPS 2012
A Better Way to Pretrain Deep Boltzmann Machines NIPS 2012
Two Distributed-State Models For Generating High-Dimensional Time Series JMLR 2011
Generating more realistic images using gated MRF's NIPS 2010
Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine NIPS 2010
Learning to combine foveal glimpses with a third-order Boltzmann machine NIPS 2010
Gated Softmax Classification NIPS 2010
3D Object Recognition with Deep Belief Nets NIPS 2009
Replicated Softmax: an Undirected Topic Model NIPS 2009
Zero-shot Learning with Semantic Output Codes NIPS 2009
Using matrices to model symbolic relationship NIPS 2008
Implicit Mixtures of Restricted Boltzmann Machines NIPS 2008
The Recurrent Temporal Restricted Boltzmann Machine NIPS 2008
Generative versus discriminative training of RBMs for classification of fMRI images NIPS 2008
A Scalable Hierarchical Distributed Language Model NIPS 2008
Modeling image patches with a directed hierarchy of Markov random fields NIPS 2007
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NIPS 2007
Modeling Human Motion Using Binary Latent Variables NIPS 2006
Reinforcement Learning with Factored States and Actions JMLR 2004
Energy-Based Models for Sparse Overcomplete Representations JMLR 2003