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burakkanber.com | ||
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tomhume.org
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| | | | | I don't remember how I came across it, but this is one of the most exciting papers I've read recently. The authors train a neural network that tries to identify the next in a sequence of MNIST samples, presented in digit order. The interesting part is that when they include a proxy for energy usage in the loss function (i.e. train it to be more energy-efficient), the resulting network seems to exhibit the characteristics of predictive coding: some units seem to be responsible for predictions, others for encoding prediction error. | |
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markodenic.com
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| | | | | Free programming books, algorithms, public APIs, and much more. | |
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sander.ai
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| | | | | Slides for my talk at the Deep Learning London meetup | |
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zserge.com
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| | | Neural network and deep learning introduction for those who skipped the math class but wants to follow the trend | ||
