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iclr.cc | ||
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www.ntentional.com
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| | | | | Highlights from my favorite Deep Learning efficiency-related papers at ICLR 2020 | |
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coen.needell.org
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| | | | | In my last post on computer vision and memorability, I looked at an already existing model and started experimenting with variations on that architecture. The most successful attempts were those that use Residual Neural Networks. These are a type of deep neural network built to mimic specific visual structures in the brain. ResMem, one of the new models, uses a variation on ResNet in its architecture to leverage that optical identification power towards memorability estimation. M3M, another new model, ex... | |
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dustintran.com
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| | | | | Having recently finished some papers with Rajesh Ranganath and Dave Blei on variational models [1] [2], I'm now a bit free to catch up on my reading of recen... | |
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www.nicktasios.nl
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| | | In the Latent Diffusion Series of blog posts, I'm going through all components needed to train a latent diffusion model to generate random digits from the MNIST dataset. In this first post, we will tr | ||
