In Yann Lecun says that the brain doesn't do reconstruction, that it doesn't reconstruct an input from an embedding. This seems very counter intuitive to me... Why not? What are dreams then? Aren't they reconstructions of input signals (images, sounds etc.) from some sort of embeddings?（01:12:00 - 01:54:23） - 07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE

In Yann Lecun says that the brain doesn't do reconstruction, that it doesn't reconstruct an input from an embedding. This seems very counter intuitive to me... Why not? What are dreams then? Aren't they reconstructions of input signals (images, sounds etc.) from some sort of embeddings?（01:12:00 - 01:54:23）
07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE

Course website: http://bit.ly/DLSP21-web
Playlist: http://bit.ly/DLSP21-YouTube
Speaker: Yann LeCun

Chapters
00:00:00 – Welcome to class
00:06:55 – Training methods revisited
00:08:03 – Architectural methods
00:12:00 – 1. PCA
00:18:04 – Q&A on Definitions: Labels, (un)conditional, and (un, s...
Course website: http://bit.ly/DLSP21-web
Playlist: http://bit.ly/DLSP21-YouTube
Speaker: Yann LeCun

Chapters
00:00:00 – Welcome to class
00:06:55 – Training methods revisited
00:08:03 – Architectural methods
00:12:00 – 1. PCA
00:18:04 – Q&A on Definitions: Labels, (un)conditional, and (un, self)supervised learning
00:25:31 – 2. Auto-encoder with Bottleneck
00:27:40 – 3. K-Means
00:34:40 – 4. Gaussian mixture model
00:41:37 – Regularized EBM
00:52:08 – Yann out of context
00:53:24 – Q&A on Norms and Posterior: when the student is thinking too far ahead
00:53:58 – 1. Unconditional regularized latent variable EBM: Sparse coding
01:06:10 – Sparse modeling on MNIST & natural patches
01:12:18 – 2. Amortized inference
01:17:02 – ISTA algorithm & RNN Encoder
01:26:56 – 3. Convolutional sparce coding
01:36:37 – 4. Video prediction: very briefly
01:39:22 – 5. VAE: an intuitive interpretation
01:48:34 – Helpful whiteboard stuff
01:52:35 – Another interpretation

#PyTorch #NYU #Yann LeCun #Deep Learning #neural networks

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

– Welcome to class

07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE
2021年08月12日　
00:00:00 - 01:54:23
I am awake at as well 🤣Joke aside, 2021 videos are quite different from 2020, which is a great treat! I am being introduced to VAE from EBM's R(z). Also, thanks for sharing the homework 3 questions which help me to think and understand EMB better. Thank you Professor Yann and Professor Alfredo! 🥰 - 07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE

I am awake at as well 🤣Joke aside, 2021 videos are quite different from 2020, which is a great treat! I am being introduced to VAE from EBM's R(z). Also, thanks for sharing the homework 3 questions which help me to think and understand EMB better. Thank you Professor Yann and Professor Alfredo! 🥰

07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE
2021年08月12日　
00:52:09 - 01:54:23
In Yann Lecun says that the brain doesn't do reconstruction, that it doesn't reconstruct an input from an embedding. This seems very counter intuitive to me... Why not? What are dreams then? Aren't they reconstructions of input signals (images, sounds etc.) from some sort of embeddings? - 07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE

In Yann Lecun says that the brain doesn't do reconstruction, that it doesn't reconstruct an input from an embedding. This seems very counter intuitive to me... Why not? What are dreams then? Aren't they reconstructions of input signals (images, sounds etc.) from some sort of embeddings?

07L – PCA, AE, K-means, Gaussian mixture model, sparse coding, and intuitive VAE
2021年08月12日　
01:12:00 - 01:54:23
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