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Geoffrey Hinton
Backpropagation and Deep Learning in the Brain
The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design
ARCHITECTS of INTELLIGENCE for Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS of INTELLIGENCE
Fast Neural Network Emulation of Dynamical Systems for Computer Animation
Neural Networks for Machine Learning Lecture 4A Learning To
Lecture Notes Geoffrey Hinton
The Dartmouth College Artificial Intelligence Conference: the Next
CNN Encoder to Reduce the Dimensionality of Data Image For
The History Began from Alexnet: a Comprehensive Survey on Deep Learning Approaches
Manitest: Are Classifiers Really Invariant? 1
Geoffrey Hinton Department of Computer Science University of Toronto
Combining Learned Representations for Combinatorial Optimization
Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings
Deep Learning - Review Yann Lecun, Yoshua Bengio & Geoffrey Hinton
Backpropagation: 1Th E Basic Theory
Deep Learning: State of the Art (2020) Deep Learning Lecture Series
DEPARTMENT of COMPUTER SCIENCE, University of Toronto
A Short History of Artificial Intelligence, Machine Learning, and Deep Learning*
Top View
Prof. Geoffrey Hinton
Where We're At
Neural Networks & Convolutional Neural Networks
Matrix Capsules with Em Routing
Turing and Computationalism
A Timeline of Artificial Intelligence
How to Represent Part-Whole Hierarchies in a Neural Network
Geoffrey Hinton
The Deep Learning Revolution
Don't Worry About the Computers Taking Over . . . Until They Ask 'Why'
Deep Learning
The Fourth Paradigm 10 Years on }
Dark Knowledge
How to Do Backpropagation in a Brain
Backpropagation and the Brain the Structure That Is Only Implicit in the Raw Sensory Input
Faculty Highlights
Artificial Intelligence in Robotics
The Third of Wave of AI
Continual Learning for Natural Language Generation in Task-Oriented Dialog Systems
Bounded Rationality and Artificial Intelligence
The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence COLLOQUIUM PAPER
Deep Learning Explained What It Is, and How It Can Deliver Business Value to Your Organization
Machine Learning
How to Do Backpropagation in a Brain
An Executive's Guide to AI
Contents U U U
My Reading List for Deep Learning!
Implicit Generation and Generalization with Energy-Based Models
Lookahead Optimizer: K Steps Forward, 1 Step Back
The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence
Artificial Intelligence and the Singularity
Yoshua Bengio, Yann Lecun, Geoffrey Hinton
Deep Learning
Does Alphago Actually Play Go? Concerning the State Space of Artificial Intelligence ______
Depths of Learning
1.3 the History of Artificial Intelligence
On the Origin of Deep Learning
CNN Architectures
Arxiv:1807.08169V1 [Cs.LG]
Deep Learning and Embodiment
Convolutional Neural Networks the CIFAR-10 and CIFAR-100 Are Labeled Subsets of the 80 Million Tiny Images Dataset
Neural Networks for Machine Learning Lecture
Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
Advancing Neural Turing Machines: Learning a Solution to the Shortest Path Problem
DEPARTMENT of COMPUTER SCIENCE, University of Toronto 2009 AWARDS
Deep Convolutional Networks
GPU Kernels for Block-Sparse Weights
Deep Learning Lecture 1: Introduction
Performance Improvement of Path Planning Algorithms with Deep Learning Encoder Model
Efficient Estimation of Influence of a Training Instance
Using Fast Weights to Attend to the Recent Past
Using a Neural Net to Instantiate a Deformable Model 967
Natural Language Generation for Effective Knowledge Distillation
The BBVA Foundation Bestows Its Award on the Architect of the First Machines Capable of Learning in the Same Way As the Human Brain
Deep Learning, Past Present and Future
Neural Networks for Machine Learning Lecture 5A Why Object
Imagenet Classification with Deep Convolutional Neural Networks
CNN Encoder to Reduce the Dimensionality of Data Image for Motion Planning
Machine Learning and Computer Vision Group