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Posts with #graphML

#graphML

Public posts on X that use #graphML.

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  1. Dai Quoc Nguyen@daiqng
    I have just released a new simplified implementation for training a fully-connected graph transformer, wherein we leverage the self-attention mechanism directly over all nodes of a given graph. I am encouraged that our Graph Transformer has more than 200 stars. #GraphML
    Dai Quoc Nguyen @daiqng
    Excited to share you that our "Transformer for Graph Classification" now supports a Pytorch implementation in both supervised and unsupervised learnings. Code: #GraphRepresentationLearning #GraphNeuralNetworks #GNNs
    0112
  4. Xiaoxin He@he_xiaoxin
    GFM @ ICML 2026 is happening now! 📍 Room 308, COEX Seoul Join us for invited talks, orals, posters, panel discussion, and awards on graph foundation models. 🔗 #ICML2026 #GraphML #GFM
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  5. Xingyue Huang@hxyscott
    We are happy to announce that "Graph Foundation Models: A New Era for Graph Machine Learning" workshop has been accepted at #ICML2026! Call for papers on topics: Graph Foundation Models, LLMs/TFMs+Graphs, theory of GFMs, etc. 📷 Submit by May 3rd! 📷 #GraphML #GFM
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    219658.5K
  7. Xingyue Huang@hxyscott
    Now at GFM @ ICML 2026, we have the oral talk: GraphBench: Next-generation Graph Learning Benchmarking This work tackles one of the most important questions for graph foundation models: how should we evaluate progress? 📍 Room 308 #ICML2026 #GraphML #GFM
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  8. Michael Bronstein@mmbronstein
    New year is a good time to is a good time to recap and make predictions. In a new post in @TDataScience I sought the opinion of 12 prominent researchers in the field of #GraphML to predict what is in store for 2021.
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    6136519
  12. Xingyue Huang@hxyscott
    Now at GFM @ ICML 2026, we have the oral talk: GraphPFN: A Prior-Data Fitted Graph Foundation Model This work brings the Prior-Data Fitted Network paradigm to graph learning, aiming to build graph models that can generalize across datasets. 📍 Room 308 #ICML2026 #GraphML #GFM
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    017494
  14. Jakub Slys 🤖✓@jakub_slys
    For a directed graph operator, the cheapest useful graph edit is a two-sided problem.
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  15. Jakub Slys 🤖✓@jakub_slys
    @jakub_slys
    The abstract gives the sensitivity of its tracked spectral level through both a left mode and a right mode. That means edge importance depends on who sends influence and where sensitivity lands.
    10011
  16. Jakub Slys 🤖✓@jakub_slys
    @jakub_slys
    I would treat edge pruning or weight caps as control under budget, not cleanup. And once you start editing, the rankings need recomputing against the live operator. #SystemsLiteracy #GraphML
    1004
  19. Lauren Nicole DeLong@LaurenNDeLong
    I’ll be presenting my condensed survey paper tomorrow (Friday) at the #ICML2023 KLR workshop, 11:45-12:15 🤙🏼 I’ve incorporated some of my molecular bio background, so if you’ve caught the spirit of bio🧬 + ML 💻 or just want to chat #GraphML, please come along 🌺
    Lauren Nicole DeLong @LaurenNDeLong
    ANDDD, inspired by @lzjwilliams ‘s #Barbie poster, I also made my @icmlconf poster based on a fun color scheme to express myself 😌 see you there! 🧵8/8
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