Pascal Welke
@pascalwelke.bsky.social
140 followers 78 following 15 posts
Graph Machine Learning and Graph Mining Assistant Professor (Lecturer) in Data Science Lancaster University Leipzig https://pwelke.de
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pascalwelke.bsky.social
We show that message passing neural networks (MPNNs) are implicitly trained to respect graph functional distances, and introduce the weighted Weisfeiler Leman Labeling Tree (WILT) to identify subgraphs that MPNNs consider functionally important.
pascalwelke.bsky.social
Attended my first @netsciconf.bsky.social last week and it was amazing!

A highlight was the HONAI satellite that brought together the network science and machine learning communities.

...and who needs NeurIPS mugs if one can have NetSci toilet paper?
Reposted by Pascal Welke
maxthiessen.bsky.social
After a break in April we welcome all of you to the next session of GLOW🌟 next week!

Join and interact with our speakers Christian Koke (scale in GNNs) and Yonatan Sverdlov (sparse geometric MPNNs).

🗓️ May 28th, 5pm CEST on Zoom.

🌐 Details & sign-up: sites.google.com/view/graph-learning-on-weds.
pascalwelke.bsky.social
🗓 The date is out: 15/09/2025
Come meet the graph community in Porto @MLG to discuss the latest developments and ideas in the field!

💡We welcome many kinds of papers beyond regular ones such as Work-in-progress papers or Visionary (white) papers!

Submit by June 14th

mlg-europe.github.io/2025
MLG 2025
mlg-europe.github.io
pascalwelke.bsky.social
Today, I gave a talk on Expressive Graph Representations via Homomorphisms in Subhankar Mishras lab at NISER, India.

For all those (all - 50) people who missed it at the LoG Paris meetup, there is now a recording available:

www.niser.ac.in/~smishra/eve...

Thanks for the invite!
www.niser.ac.in
Reposted by Pascal Welke
maxthiessen.bsky.social
GLOW is returning on 𝗠𝗮𝗿𝗰𝗵 𝟮𝟲𝘁𝗵, 𝟱𝗽𝗺 𝗖𝗘𝗧 with a special guest: @petar-v.bsky.social 🌟

He will lecture on LLMs as GNNs – a topic which received quite some attention at our last session.

Specifically, we will learn how Graph ML tools can help understand LLM generalisation
Reposted by Pascal Welke
neumannstefan.com
I am hiring for a Ph.D. student to work in the areas of social network analysis, algorithms and fair machine learning.

Please apply and join our highly motivated team.

For more information please see the call: neumannstefan.com/hiring/
Call for Doctoral Students in Social Network Analysis, Algorithms and Fair Machine Learning
neumannstefan.com
pascalwelke.bsky.social
In two hours (i.e., 5pm CET), we'll have the first GLOW meeting of the year. Join us for two interesting talks and detailed discussions!
maxthiessen.bsky.social
🌟 GLOW 2025 kicks off with a great session in January!

Join and interact with our speakers Clayton Sanford (on transformers for graph algorithms) and Derek Lim (on graph metanetworks).

🗓️ Jan 15th, 5pm CET on Zoom.

🌐 Details & sign-up: sites.google.com/view/graph-learning-on-weds.
Reposted by Pascal Welke
nicolaskeriven.bsky.social
We organise a thematic day on Graph Machine Learning and Graph Neural Networks at IHP in Paris on March 31st. Please consider submitting abstracts!

It'll be fun 🤓

Free mandatory registration:
gdr-iasis.cnrs.fr/reunions/app...
Apprentissage et Graphes - GdR IASIS
Lire la suite
gdr-iasis.cnrs.fr
Reposted by Pascal Welke
maxthiessen.bsky.social
🌟 GLOW 2025 kicks off with a great session in January!

Join and interact with our speakers Clayton Sanford (on transformers for graph algorithms) and Derek Lim (on graph metanetworks).

🗓️ Jan 15th, 5pm CET on Zoom.

🌐 Details & sign-up: sites.google.com/view/graph-learning-on-weds.
Reposted by Pascal Welke
maxthiessen.bsky.social
Ever needed a graph neural network with maximal expressivity on almost all molecules (aka 𝗼𝘂𝘁𝗲𝗿𝗽𝗹𝗮𝗻𝗮𝗿 graphs)?

Turns out you only need a simple graph transformation called 𝐶𝐴𝑇!

Short talk: youtube.com/watch?v=AW6C...
TMLR paper: openreview.net/forum?id=XxbQA
pascalwelke.bsky.social
Is Expressivity Essential for the Predictive Performance of Graph Neural Networks?

Spoiler alert: No.

Check out our poster at the Sci4DL workshop, today at 4.30pm, West Meeting Room 205-207

Paper: pwelke.de/publications...

Poster: pwelke.de/publications...
TL;DR More expressive GNNs outperform less expressive GNNs not due to expressivity. 

Pdf Version of the poster, as well as the paper is available at https://pwelke.de
pascalwelke.bsky.social
Oral at 10.20 am in West Exhibit Hall C
Poster #3009 at 11am in East Exhibit Hall A-C
pascalwelke.bsky.social
Today at NeurIPS:

Weisfeiler and Leman go Loopy: A New Hierarchy for Graph Representational Learning

Cycles are important for predictive tasks on chemical molecules. We allow message passing along neighboring paths. Our architecture can subgraph-count cycles and homomorphism-count cactus graphs.
Visual depiction of r-lGIN: During preprocessing, we calculate the path neighborhoods Nr (v) for each node v in the graph G. Paths of varying lengths are processed separately using simple GINs, and their embeddings are pooled to obtain the final graph embedding. The forward complexity scales linearly with the sizes of Nr (v), enabling efficient computation on sparse graphs.
pascalwelke.bsky.social
Give yourself an early Christmas present: Visit GLOW and learn about two amazing papers and interact with their authors!
ffabffrasca.bsky.social
🌟 GLOW is coming back in December with amazing speakers: Emily Jin and @joshsouthern.bsky.social !

🗓️ Dec 18th @ 17 CET on Zoom, don't miss that!

🌐 Find more here: sites.google.com/view/graph-l...
pascalwelke.bsky.social
The slides are on my homepage. Official recordings of the event will follow soon.

pwelke.de/presentation...
pwelke.de
pascalwelke.bsky.social
Had an incredible time at the Learning on Graphs meetup in Paris! Amazing energy, awesome presentations, and lovely posters. I was honored to give a keynote on graph representation learning via homomorphisms and loved the insightful questions and vibrant discussions.