[HN Gopher] Tutorial on diffusion models for imaging and vision
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       Tutorial on diffusion models for imaging and vision
        
       Author : Anon84
       Score  : 56 points
       Date   : 2024-09-10 19:59 UTC (3 hours ago)
        
 (HTM) web link (arxiv.org)
 (TXT) w3m dump (arxiv.org)
        
       | redblacktree wrote:
       | Does something similar exist for LLM/GPT?
       | 
       | Edit to add: I'm mostly interested in this aspect:
       | 
       | "The target audience of this tutorial includes [those] who are
       | interested in [...] applying these models to solve other
       | problems."
        
         | roninorder wrote:
         | Andrej Karpathy has very good video tutorials on how to write
         | your own GPT: https://www.youtube.com/watch?v=kCc8FmEb1nY
        
         | BaculumMeumEst wrote:
         | Andrej Karpathy has a youtube playlist:
         | 
         | https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs...
         | 
         | He is building new learning materials under his new company
         | "Eureka Labs":
         | 
         | https://eurekalabs.ai
         | 
         | Sebastian Raschka's book "Build a Large Language Model (From
         | Scratch) just released:
         | 
         | https://www.manning.com/books/build-a-large-language-model-f...
         | 
         | All of these resources are _excellent_.
        
       | GaggiX wrote:
       | A very useful guide about how diffusion models work and
       | implementation: https://keras.io/examples/generative/ddim/
       | 
       | I find the explanation in this article very intuitive.
        
       | yinser wrote:
       | > see tutorial on diffusion > get excited > it's all math in
       | latex > despair
        
         | whimsicalism wrote:
         | the math is learnable and with gpt nowadays, extremely so
        
         | slashdave wrote:
         | Latex is great in this case, because the equations are all
         | written out clearly.
         | 
         | If you want to understand diffusion, it's a little difficult to
         | avoid math.
        
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       (page generated 2024-09-10 23:00 UTC)