… classified as moving towards hand-designing architectural biases in the networks themselves
[95]… , goes a long way towards explaining many of the recent advances in neural networks. …

… (2) This preferred complexity is observable in networks with random weights from an un… a
signal towards low frequencies. Here, the parameter space of NNs is biased towards functions …

… That is, we will define network generators that yield networks with random graphs, subject
to different human-… Faster R-CNN: Towards real-time object detection with region proposal …

… transcends science - debating them probably has some dimension of collective soul
searching as our field slowly gravitates toward data science, away from complexity science. So, …

… Network Coding (RLNC) [13], by allowing the nodes to choose their linear coefficients
independently and uniformly at random … in the network to transmit different combinations towards a …

… we evolve is based on random Boolean networks (RBNs). Basically, this is a modification
of our stochastic cellular automata, but with the connectivity between the cells being random. …

… , is the first method that was explicitly designed towards identifying the critical nodes in a
network under limited computational resources. It is known that the concepts of influence and …

… The algorithm is equivalent to ensemble an infinite number of random models … toward
adversarial attacks and show that adding noise layers is equivalent to training the original network …

… coincides with phase transitions in classical random Boolean networks and the Ising
model, … in both cases is moving towards a chaotic or an ordered regime. Additionally, bigger …

… Toward that end, the method uses the digital implementation of the very same PRNG that
generated random parameters at training time. In practice, at run time, the same set of random …