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Facebook’s New Open Source Framework For Training Graph-Based ML Models

GTN Facebook
Facebook recently open-sourced the graph transformer networks (GTN) framework for effectively training graph-based learning models. In this case, GTN will be used in automatic differentiation of weighted finite-state transducers (WFSTs), which is an expressive and powerful graph. With GTN, researchers can easily construct WFSTs, visualize them, and perform operations on them This framework enables the separation of graphs from operations on them that helps in exploring new structured loss functions and which in turn makes the encoding of prior knowledge on learning algorithms easier. Further, in a paper published by Awni Hannun, Vineel Pratap, Jacob Kahn & Wei-Ning Hsu of the Facebook AI Research, in this regard, proposed a convolutional WFST layer to be used in the interior of a de
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Picture of Shraddha Goled
Shraddha Goled
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at shraddha.goled@analyticsindiamag.com.
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