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Degree-based stratification of nodes in Graph Neural NetworksAmeen Ali, Lior Wolf, Hakan CevikalpDespite much research, Graph Neural Networks (GNNs
Technical intelligence on neural network architectures, deep learning breakthroughs, transformer models, neuromorphic computing, and the computational foundations of artificial intelligence
In my last post, I briefly discussed the infuriating fact that a neural network, even when deeply flawed, will often “work” in the sense that it’ll do above-random at classification or a generative network might create things that may somet
Never been one to let the carrier drop Sheer rambles on about this, that, and the other. « One huge problem Root causes » Neural networks and politics So, as most of you know, I’ve spent a fair amount of time lately researching natural and artificial neural networks. I had a interesting thought the other day. While I am so far to the left politically that they don’t have a good label to hang on me – I want to redesign the resource allocation system, I think it’s possible to get almost everyone
We've developed an approach to generate 3D adversarial objects that reliably fool neural networks in the real world, no matter how the objects are looked at
Recent work has shown that the performance of spiking neural networks (SNNs) on temporally complex tasks improves significantly when axonal delays are treated a
This paper introduces a categorical and homotopical framework that formalizes deep neural networks using topos theory, stacks, and homotopical invariants
01/03/22 - One major drawback of deep convolutional neural networks (CNNs) for use in safety critical applications is their black-box nature
Abstract neural network (ANN) models, also known variously as artificial neural networks, connectionism, parallel distributed processing (PDP), perceptrons, backpropagation networks, deep networks, AI (artificial intelligence) models, and ML (machine learning), represent a large class of models that include the core mechanism of distributed processing performed by interconnected neuron-like processing elements (units