An Efficient Architecture for Graph Problems [Paper] (VLDB 2022) ByteGNN: Efficient Graph Neural Network Training at Large Scale [Paper] (CIKM 2022) AdaGCL: Adaptive Subgraph Contrastive Learning to ...

This repo contains an example implementation of the Simple Graph Convolution (SGC) model, described in the ICML2019 paper Simplifying Graph Convolutional Networks. SGC removes the nonlinearities and ...

Since it's a new year, I thought I'd answer some recurring questions on how we decide what letters we publish. Our policy is simple: The word limit is 300 words for all letters. We don’t allow ...

Learn some of the basic skills needed to make neat and carefully crafted models and folded paper forms. We will create quick response models to test techniques. Moving on to examine a site to create a ...

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Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, ...

The title should be concise, omitting terms that are implicit and, where possible, be a statement of the main result or conclusion presented in the manuscript. Abbreviations should be avoided within ...

(Curiously, non-stretched graphene is a material that hosts a Dirac fermion, so its power law is denoted by the orange line in the graph above.) An older study also revealed some unusual ...