[HN Gopher] TensorFlow Graph Neural Networks
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TensorFlow Graph Neural Networks
Author : 0xedb
Score : 82 points
Date : 2021-11-18 18:33 UTC (4 hours ago)
(HTM) web link (blog.tensorflow.org)
(TXT) w3m dump (blog.tensorflow.org)
| technologia wrote:
| I'm glad to see support for GNNs with tensorflow. Working with
| gnns for the past few years, personally for me it gets tiring to
| roll my own framework.
| claytonjy wrote:
| what's the state of GNN support elsewhere? does everyone else
| also roll their own, or are folks using Pytorch or something
| else?
| rytill wrote:
| This is a big one: https://github.com/pyg-
| team/pytorch_geometric
| patagurbon wrote:
| DGL is the other big one, it supports several frameworks (at
| least PyTorch and MXNet).
| H8crilA wrote:
| What's an example problem for which such networks work well?
| lmeyerov wrote:
| Think of it as an ensemble for blending your normal NN
| features (ex: RNN for time/clickstreams) with a model that
| can also leverage useful graph features (document citations,
| app logins, chemicals connecting, social graphs).
|
| We think a lot about security/fraud and digital journeys,
| where NN + xgboost are popular in general, and graph for
| looking at broader structure, so GNNs enable better blending
| these concepts. For example, in analyzing malicious user
| accounts (ex: misinfo on twitter), we can get time/nlp/etc
| scores, and use the social network structure to ensure better
| propagation/blending, similar to why boosting and ensemble
| methods became popular to beginwith.
| [deleted]
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