Multilevel framework to improve accuracy and/or runtime of several network alignment algorithms. Great work during your time at @Livermore_Comp Jing! https://t.co/dm28Wc1s9Q
A great combination of theoretical analysis, examination of intuition from other domains, empirical insights, and new benchmarks for graph contrastive learning—all in one paper. Outstanding work led by Puja!
New Paper Alert #NeurIPS2022: Self-supervised learning with discrete, structured data comes with some twists! In our paper, we explore how data-centric properties known to be crucial to success of visual CL can fail to hold for graph CL. 🧵Abs:https://t.co/VLlGt7Vu4I
2. We take a deep look into graph contrastive learning and find that data-centric properties known to be crucial to the success of visual CL can fail to hold for graph CL. Paper: https://t.co/9s3YabcWuw @puja_computes@lastgoodcaesar@EkdeepL@danaikoutra
@d_metaxa Hey, just wanted to say, as another early career CS researcher and powerlifter (also newbie climber!), you might enjoy Collective Strength. They have competition-grade PL equipment and an admirable ethos https://t.co/hX0hipcxBB
@luchengSRAI@fredmorstatter@hjagadish@liuhuan@Ilsebyl Our fourth tutorial is held by Mark Andrew Heimann, Junchen Jin and Danai Koutra (@danaikoutra). The tutorial is about
+++ Network Embedding for Role Discovery: Concepts, Tools, and Applications +++.
Link:
https://t.co/9KNcKz8RVg
Structural role-based node embedding: extensive benchmarks, insights, and easy-to-use codebase. Led by undergrad alum Junchen Jin whose organization awes me 🙂 with Di Jin and @danaikoutra.
https://t.co/KsNMOC5WHX
https://t.co/FljLFGOitZ
Thanks @tangjiliang for sharing this interesting and thought-provoking work. In light of these new findings, we revisit the problem of heterophily for GNNs and discuss the reasons behind the seemingly different takeaways from different works. Check it out:
https://t.co/08FvMGb59J
@SarahJabbour_ Congrats, and glad to hear the weights are such a great outlet during your PhD :) I don't know how to do cool barbell movements but otherwise I relate
@ElissaWelle I went through this too. So glad you're a) talking about it, and b) supporting others in similar places. And also glad you did stick around and produce some amazing work :)
@abuyukcakir There are so many worthwhile paths to take in life with or without a PhD. I look forward to seeing which of them you'll take next! The potential is truly unbounded
@abuyukcakir Lol that guitar is yours to keep if you like! If not, of course it's a great idea to have it circle around the GEMS Lab a while longer (I hadn't even considered this but I love this idea too)
https://t.co/QuBGRnIdQx Use node proximities to learn embeddings modeling node proximity OR structural roles. Kind of like using 🍕dough to make 🍕OR cinnamon rolls. @JingZhu85095487 did an outstanding job on this project and will present it today at #SDM2021
@graph_ Nevertheless, congratulations on the defense of an impressive body of work for your PhD, Dr. Anton (oops, look what I did there, silly American that's me)