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NYU Deep Learning SP21

by Alfredo Canziani (冷在)

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Playlist•33 videos•205,324 views

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PLAY ALL

NYU Deep Learning SP21

33 videos

205,324 views

Last updated on Jun 6, 2022

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Alfredo Canziani (冷在)

Play all

NYU Deep Learning SP21

by Alfredo Canziani (冷在)

Playlist•33 videos•205,324 views

Play all

50:18

Now playing

01 – History and resources

Alfredo Canziani (冷在)

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111K views • 4 years ago

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1:51:04

Now playing

01L – Gradient descent and the backpropagation algorithm

Alfredo Canziani (冷在)

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62K views • 3 years ago

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1:01:54

Now playing

02 – Neural nets: rotation and squashing

Alfredo Canziani (冷在)

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32K views • 4 years ago

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1:42:27

Now playing

02L – Modules and architectures

Alfredo Canziani (冷在)

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24K views • 3 years ago

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1:05:48

Now playing

03 – Tools, classification with neural nets, PyTorch implementation

Alfredo Canziani (冷在)

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23K views • 4 years ago

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1:59:48

Now playing

03L – Parameter sharing: recurrent and convolutional nets

Alfredo Canziani (冷在)

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22K views • 3 years ago

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51:41

Now playing

04L – ConvNet in practice

Alfredo Canziani (冷在)

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11K views • 3 years ago

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1:09:13

Now playing

04.1 – Natural signals properties and the convolution

Alfredo Canziani (冷在)

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15K views • 4 years ago

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1:05:36

Now playing

04.2 – Recurrent neural networks, vanilla and gated (LSTM)

Alfredo Canziani (冷在)

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23K views • 4 years ago

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1:51:31

Now playing

05L – Joint embedding method and latent variable energy based models (LV-EBMs)

Alfredo Canziani (冷在)

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26K views • 3 years ago

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1:01:05

Now playing

05.1 – Latent Variable Energy Based Models (LV-EBMs), inference

Alfredo Canziani (冷在)

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17K views • 4 years ago

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10:42

Now playing

05.2 – But what are these EBMs used for?

Alfredo Canziani (冷在)

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10K views • 4 years ago

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1:48:54

Now playing

06L – Latent variable EBMs for structured prediction

Alfredo Canziani (冷在)

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10K views • 3 years ago

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1:04:49

Now playing

06 – Latent Variable Energy Based Models (LV-EBMs), training

Alfredo Canziani (冷在)

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10K views • 4 years ago

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1:54:23

Now playing

07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE

Alfredo Canziani (冷在)

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10K views • 3 years ago

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56:42

Now playing

07 – Unsupervised learning: autoencoding the targets

Alfredo Canziani (冷在)

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7.8K views • 4 years ago

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1:54:44

Now playing

08L – Self-supervised learning and variational inference

Alfredo Canziani (冷在)

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9.7K views • 3 years ago

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1:00:35

Now playing

08 – From LV-EBM to target prop to (vanilla, denoising, contractive, variational) autoencoder

Alfredo Canziani (冷在)

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8.2K views • 4 years ago

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2:00:29

Now playing

09L – Differentiable associative memories, attention, and transformers

Alfredo Canziani (冷在)

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9.2K views • 3 years ago

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1:07:51

Now playing

09 – AE, DAE, and VAE with PyTorch; generative adversarial networks (GAN) and code

Alfredo Canziani (冷在)

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18K views • 4 years ago

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1:36:13

Now playing

10L – Self-supervised learning in computer vision

Alfredo Canziani (冷在)

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32K views • 3 years ago

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1:12:01

Now playing

10 – Self / cross, hard / soft attention and the Transformer

Alfredo Canziani (冷在)

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36K views • 3 years ago

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1:55:04

Now playing

11L – Speech recognition and Graph Transformer Networks

Alfredo Canziani (冷在)

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11K views • 3 years ago

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57:34

Now playing

11 – Graph Convolutional Networks (GCNs)

Alfredo Canziani (冷在)

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9K views • 3 years ago

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1:57:56

Now playing

12L – Low resource machine translation

Alfredo Canziani (冷在)

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3.9K views • 3 years ago

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1:10:23

Now playing

12 – Planning and control

Alfredo Canziani (冷在)

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5.6K views • 3 years ago

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1:51:33

Now playing

13L – Optimisation for Deep Learning

Alfredo Canziani (冷在)

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7.3K views • 3 years ago

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1:01:22

Now playing

13 – The Truck Backer-Upper

Alfredo Canziani (冷在)

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3.3K views • 3 years ago

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2:12:36

Now playing

14L – Lagrangian backpropagation, final project winners, and Q&A session

Alfredo Canziani (冷在)

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5.8K views • 3 years ago

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1:14:45

Now playing

14 – Prediction and Planning Under Uncertainty

Alfredo Canziani (冷在)

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4.7K views • 3 years ago

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3:45:28

Now playing

AI2S Xmas Seminar - Dr. Alfredo Canziani (NYU) - Energy-Based Self-Supervised Learning

AI Student Society

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3.2K views • Streamed 3 years ago

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56:52

Now playing

09P – Contrastive joint embedding methods (JEMs) for self-supervised learning (SSL)

Alfredo Canziani (冷在)

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9.2K views • 3 years ago

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1:05:28

Now playing

10P – Non-contrastive joint embedding methods (JEMs) for self-supervised learning (SSL)

Alfredo Canziani (冷在)

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4.4K views • 3 years ago

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