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Found 3 papers, 1 papers with code
Intelligent Matrix Exponentiation
We present a novel machine learning architecture that uses the exponential of a single input-dependent matrix as its only nonlinearity.
Temporal Coding in Spiking Neural Networks with Alpha Synaptic Function: Learning with Backpropagation
The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli.
SO(8) Supergravity and the Magic of Machine Learning
Using de Wit-Nicolai $D=4\;\mathcal{N}=8\;SO(8)$ supergravity as an example, we show how modern Machine Learning software libraries such as Google's TensorFlow can be employed to greatly simplify the analysis of high-dimensional scalar sectors of some M-Theory compactifications.
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