Robotics & Perception/Unsupervised Learning
[CS294 Pieter Abbeel] 5. Implicit Models - GANs
이 글은 필자가 Pieter Abbeel 의 Deep Unsupervised Learning 2020을 듣고 정리한 글입니다. 🗿Implicit Models? 🗿Original GAN 🗿GAN Progression
[CS294 Pieter Abbeel] 4. Latent Variable Models - Variational AutoEncoder (VAE)
이 글은 필자가 Pieter Abbeel 의 Deep Unsupervised Learning 2020을 듣고 정리한 글입니다. 🖲️ Training Latent Variable Models 🖲️ Variations of VAE 🖲️ Related Ideas
[CS294 Pieter Abbeel] 3. Likelihood Models: Flow Models
이 글은 필자가 Pieter Abbeel 의 Deep Unsupervised Learning 2020을 듣고 정리한 글입니다. This lecture deal with a latent representation to get a density model $p_\theta(x)$. 🪸 Foundations of Flows (1-D) 🪸 2-D Flows 🪸 N-D Flows 🪸 Dequantization
[CS294 Pieter Abbeel] 2. Likelihood Models: Autoregressive Models
이 글은 필자가 Pieter Abbeel 의 Deep Unsupervised Learning 2020을 듣고 정리한 글입니다. This lecture is about how to get the data distribution, which means the primitive way of generative models. Generative models first came up with histograms, which is the basic model of the Likelihood-based model. And then for the neural approach, they use autoregressive models. 🫠 Likelihood-based models 🫠 Sampling-based: Hist..
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[CS294 Pieter Abbeel] 1. Intro
이 글은 필자가 Pieter Abbeel 의 Deep Unsupervised Learning 2020을 듣고 정리한 글입니다. This lecture shares what is the goal, pursuit of deep unsupervised learning By Deep Unsupervised Learning, Capture rich patterns in raw data with deep networks in a label-free way → But how? Recreate raw data distribution → Generative models "Puzzle" tasks that require semantic understanding → Self-supervised Learning With Pu..
[CS294 Pieter Abbeel] Deep Unsupervised Learning Contents
이 글은 필자가 Pieter Abbeel 의 Deep Unsupervised Learning 2020을 듣고 정리한 글입니다. Goal: Think the intuition of perceptions for robot. How will I lead my research on this perspective? Contents Intro Autoregressive Models 2h 28m Flow Models 1h 57m Latent Variable Models 2h 20m Implicit Models / Generative Adversarial Networks 2h 33m Self-Supervised Learning / Non-Generative Representation Learning 2h 10m Str..