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filmicworlds.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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techrvw.com
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| | | | | The Xiaomi Pocophone F1 is a smartphone that is very interesting! The looks are good but can be better. The specs are good and they are almost on top of the list! Battery life is good and Xiaomi says you can last for 2 days?! All those things are great and that at a very [...] | |
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acidbourbon.wordpress.com
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| | | | | Motivation In the previous post we discussed the possibility to use LTspice as a "plug in" into a Python/Numpy signal processing project. It works quite well: you send a numpy data vector to LTspice, let it run through the simulation and get back a numpy vector again. Everything is abstracted away nicely by the "apply_ltspice_filter.py"... | |
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www.jeremymorgan.com
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| | | Want to learn about PyTorch? Of course you do. This tutorial covers PyTorch basics, creating a simple neural network, and applying it to classify handwritten digits. | ||
