GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks Interesting pre-training training framework for GNNs, based on learnable prompts. It reduces labeling needs and boosts downstream task performance. https://
arxiv.org/abs/2302.08043
@maximelabonne
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GraphPrompt: Unified Pre-Training Framework for Graph Neural Networks
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Graph Neural Networks for Optimization and Scheduling Solutions
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Not directly: I'm interested in this field in general because there are a lot of cool applications, like optimizing schedules. But yes, I'm also interested in building a GNN that acts as a solver or just helps with optimization in general, like https://
arxiv.org/pdf/2209.12288
.pdf
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Convex Optimization Comprehensive Resource PDF Available
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Received this morning! Convex Optimization is widely regarded as the most comprehensive resource on convex optimization. If you're interested, here's the full pdf version: https://
web.stanford.edu/~boyd/cvxbook/ -
GPT-Based Synthetic Tabular Data Generation Library
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Cool new #GPT-based approach to synthetic tabular data generation. It shows great results compared to the excellent SDV library. Library: https://
github.com/avsolatorio/re
altabformer
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ML Professional Launches GNN Book, Joins JPMorgan UK Team
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Back on Twitter after a few chaotic months! A few updates: – I moved to the UK and joined an excellent machine learning team @jpmorgan – I'm publishing a book about Graph Neural Networks for practitioners Stay tuned for more 🙂