📚 Back from ICML with a summary of Graph ML papers! Latest about Graph Transformers, Theory, Generative Models, Geometry, Materials and Proteins, a few cool applications, and extra photos from Hawaii to make it less boring 🙂 mgalkin.medium.com/graph-machine-…

📢 Exciting news! We're presenting our paper "On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks" at ACM CIKM 2023 as a long paper (oral). Check out the preprint: arxiv.org/abs/2212.02374. The code is here: github.com/jhonygiraldo/S…. 📚 #GNN

Excited to announce that we will be presenting our paper "Adapting Neural Link Predictors for Data-Efficient Complex Query Answering" at NeurIPS Conference Done with the most amazing researchers - Pasquale Minervini Daniel Daza Michael Cochez Isabelle Augenstein paper: arxiv.org/abs/2301.12313

In knowledge graphs, the triple representation (subject, predicate, object) tells only a part of the story. Join us at #CIKM2023 to learn about more expressive paradigms and the interesting prediction problems that we can solve with them!

In this exciting call, we also have an opening for an assistant professor in data engineering. Check it out.

Interesting to see GPT 🔁 DALL-E following the second law of thermodynamics

Thanks Bo Xiong, Mojtaba Nayyeri, Michael Cochez, I learned a lot from this experience! Our slides are now online at kg-beyond-triple.github.io

I'm at #NeurIPS2023 for the first time! With my collaborators, we'll be presenting 🕵️CQD-A: A data efficient method for answering knowledge graph queries arxiv.org/abs/2301.12313 🍇 GRAPES: Scaling GNN training with GFlowNets arxiv.org/abs/2310.03399 Feel free to reach out!

If you’re going to #NeurIPS2023, check out our poster GRAPES in GLFrontiers workshop (December 15th)! 🍇 GRAPES is a GFlowNet-based adaptive graph sampling method to scale GNNs to large graphs. Paper: arxiv.org/abs/2310.03399

Our work on embedding multimodal biomedical knowledge graphs is now published at the Journal of Biomedical Semantics BMC! Read the paper here: doi.org/10.1186/s13326…

It's going to happen! What? Generative Modeling Summer School 2024 (#GeMSS24)! When: June 24-28, 2024 Where: Eindhoven, the Netherlands (TU Eindhoven, Brainport Eindhoven) Info: gemss.ai Application deadline: March 31, 2024 Don't wait, apply!

What excites me about Sora: imagining what we could achieve if, instead of a bunch of layers that compute attention over everything, trained with astronomical amounts of data and compute; these models had stronger biases for representing objects and relations compositionally.

Machine learning and database theory combine well: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs Read more: arxiv.org/abs/2310.04598 #nesy #graphlearning #knowledgegraph

This week, I'm presenting my work "ReWise" at SEMANTiCS Conference. We introduce a graph sampling framework to scale Relational Graph Convolutional Networks to large multimodal knowledge graphs. Check out our paper at: ebooks.iospress.nl/doi/10.3233/SS…

🚀 Don't miss Tamara Cucumides’ talk at LOG 2024 at 19h10 CET about "UnRavL: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs". openreview.net/forum?id=183Xr… Learning on Graphs Conference 2024

My PhD thesis is now available online at research.vu.nl/en/publication… I'm thankful with all my collaborators who joined me in this journey!

Congrats to all the UnRavL team for a Best Paper Honorable Mention at the 2024 Learning on Graphs Conference! UnRavL expands the types of queries that we can answer over incomplete knowledge graphs🧙 Read the paper here: openreview.net/pdf?id=183XrFq…