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1. www.nature.com › articles › nature14539Deep learning | Nature

   www.nature.com › articles › nature14539

   May 27, 2015 · Deep learning. Yann LeCun 1,2, Yoshua Bengio 3 & Geoffrey Hinton 4,5 ...

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3. scholar.google.com › citations‪Yann LeCun‬ - ‪Google Scholar‬

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   Yann LeCun. Chief AI Scientist at Facebook & Silver Professor at the Courant Institute, ... Deep learning. Y LeCun, Y Bengio, G Hinton. nature 521 (7553), 436-444, 2015.

4. Videos

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     Yann LeCun: Turing Award Lecture "The Deep Learning Revolution: The Sequel"

     Mar 11, 2021

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     Yann LeCun: Deep Learning, ConvNets, and Self-Supervised Learning | Lex Fridman Podcast #36

     Aug 31, 2019

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     1:7:19

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     The Epistemology of Deep Learning - Yann LeCun

     Feb 22, 2019

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5. atcold.github.io › NYU-DLSP21DEEP LEARNING · Deep Learning - Alfredo Canziani

   atcold.github.io › NYU-DLSP21

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   DEEP LEARNING. DS-GA 1008 · SPRING 2021 · NYU CENTER FOR DATA SCIENCE. INSTRUCTORS: Yann LeCun & Alfredo Canziani: LECTURES: Wednesday 9:30 – 11:30, Zoom: PRACTICA:

6. www.youtube.com › playlistDeep Learning Course (NYU, Spring 2020) - YouTube

   www.youtube.com › playlist

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   Deep Learning course at NYU, Spring 2020. Taught by Yann LeCun & Alfredo Canziani. With practical applications using PyTorch. ... Deep Learning course at NYU, Spring 2020. Taught by Yann LeCun ...

7. People also ask

   What does LeCun think about a neural network?

   • LeCun imagines that neural network as the controller for the whole system. It would decide what kind of predictions the world model should be making at any given time and what level of detail it should focus on to make those predictions possible, adjusting the world model as required.

   Yann LeCun’s big bet for building intelligent machines | MIT Technology

   www.technologyreview.com/2022/06/24/1054817/yann-lecun-bold-new-vision-future-ai-deep-learning-meta/

   See all results for this question

   Is there a fast learning algorithm for deep neural networks?

   • Hinton, G. E., Osindero, S. & Teh, Y.-W. A fast learning algorithm for deep belief nets. Neural Comp. 18, 1527–1554 (2006). This paper introduced a novel and effective way of training very deep neural networks by pre-training one hidden layer at a time using the unsupervised learning procedure for restricted Boltzmann machines.

   Deep learning | Nature

   www.nature.com/articles/nature14539

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   Can deep learning replace rule-based manipulation of symbolic expressions?

   • Although deep learning and simple reasoning have been used for speech and handwriting recognition for a long time, new paradigms are needed to replace rule-based manipulation of symbolic expressions by operations on large vectors 101. Krizhevsky, A., Sutskever, I. & Hinton, G. ImageNet classification with deep convolutional neural networks.

   Deep learning | Nature

   www.nature.com/articles/nature14539

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   Is supervised training of deep neural networks faster if hidden layers are Relu?

   • In Proc. 14th International Conference on Artificial Intelligence and Statistics 315–323 (2011). This paper showed that supervised training of very deep neural networks is much faster if the hidden layers are composed of ReLU. Dauphin, Y. et al. Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.

   Deep learning | Nature

   www.nature.com/articles/nature14539

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8. yann.lecun.comYann LeCun's Home Page

   yann.lecun.com

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   Welcome to Yann's home page. Silver Professor of Computer Science, Data Science, Neural Science, and Electrical and Computer Engineering, New York University. Address: Room 516, 60 Fifth Avenue, New York, NY 10011, USA. Complete course on Deep Learning, with all the material available on line including lecture and practicum videos, slide decks ...

9. www.technologyreview.com › 2022/06/24 › 1054817Yann LeCun’s big bet for building intelligent machines | MIT ...

   www.technologyreview.com › 2022/06/24 › 1054817

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   Jun 24, 2022 · So have many of LeCun’s ideas about prediction using models with different levels of detail. But when deep learning became the dominant approach in AI, many of these older ideas went out of fashion.

10. www.ted.com › talks › yann_lecun_deep_learningDeep learning, neural networks and the future of AI - TED

    www.ted.com › talks › yann_lecun_deep_learning

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    Yann LeCun, the chief AI scientist at Facebook, helped develop the deep learning algorithms that power many artificial intelligence systems today. In conversation with head of TED Chris Anderson, LeCun discusses his current research into self-supervised machine learning, how he's trying to build machines that learn with common sense (like humans) and his hopes for the next conceptual ...