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www.paepper.com | ||
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towardsdatascience.com
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| | | | | Learn how to build feedforward neural networks that are interpretable by design using PyTorch. | |
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jaketae.github.io
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| | | | | I recently completed another summer internship at Meta (formerly Facebook). I was surprised to learn that one of the intern friends I met was an avid reader of my blog. Encouraged by the positive feedback from my intern friends, I decided to write another post before the end of summer. This post is dedicated to the mandem: Yassir, Amal, Ryan, Elvis, and Sam. | |
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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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sebastianraschka.com
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| | | The PyTorch team recently announced TorchData, a prototype library focused on implementing composable and reusable data loading utilities for PyTorch. In... | ||
