Daniel Daza

Postdoc at Amsterdam UMC, working on machine learning and graphs.

[Daniel Daza @danieldazac]

It's been great to be part of this collaboration!
In my opinion a neat result: graph embeddings trained for 1-hop link prediction generalize well to complex queries, with a tiny increase in parameters and the power of t-norms and t-conorms.

[Erik Arakelyan @_kire_kara_]

Excited to announce that we will be presenting our paper "Adapting Neural Link Predictors for Data-Efficient Complex Query Answering" at @NeurIPSConf

Done with the most amazing researchers - @PMinervini @danieldazac @michaelcochez @IAugenstein

paper: https://t.co/iWkruqiLEU

[Daniel Daza @danieldazac]

@vera__pro Thanks a lot Vera! 😀

[Daniel Daza @danieldazac]

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: https://t.co/GZmLXj8JFZ

[Learning on Graphs Conference 2026 @LogConference]

🏆 Best Paper Award & Honorable Mention 🏆

Congratulations to our outstanding authors for their exceptional contributions to LoG 2024! 🎉

📜 Your work inspires the entire graph and geometric ML community!

[Daniel Daza @danieldazac]

@elan_marko Thanks Elan! I really like the work you did with StATIK :)

[Daniel Daza @danieldazac]

My PhD thesis is now available online at
https://t.co/eJnNjX33CX
I'm thankful with all my collaborators who joined me in this journey!

[Daniel Daza @danieldazac]

@_kire_kara_ Thanks Erik!! ☺️

[sirolf @sirolfg]

🚀 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". https://t.co/Ts8H3XXx5K @LogConference

[Taraneh Younesian @TYounesian]

This week, I'm presenting my work "ReWise" at @SemanticsConf.
We introduce a graph sampling framework to scale Relational Graph Convolutional Networks to large multimodal knowledge graphs.

Check out our paper at: https://t.co/ZkfNXTf3Ng

[sirolf @sirolfg]

Machine learning and database theory combine well: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs
Read more: https://t.co/b7KmSqsjnq #nesy #graphlearning #knowledgegraph

[Daniel Daza @danieldazac]

@andreimano2 @EmilevanKrieken @ChendiQian @Mniepert @chrsmrrs @zhezeng0908 @KareemYousrii @guyvdb I disagree, I think it's a good one 😄

[Daniel Daza @danieldazac]

@vera__pro @KBNLresearch Well done @vera__pro! This is very inspiring 👏

[Daniel Daza @danieldazac]

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.

[François Chollet @fchollet]

With Sora, the evidence is piling up quickly. Now we're operating at scale. And the evidence will keep piling up with new models going forward -- even faster.

And the evidence so far is resounding -- you really are looking at latent-space collages and interpolations. The inner physics model doesn't generalize to novel situations at all. It's not just that you can't use it as a reliable replacement for a fluid dynamics simulator to design a new aircraft or as a gravity simulator to design a new marble run course...

[Jakub Tomczak @jmtomczak]

It's going to happen! What? Generative Modeling Summer School 2024 (#GeMSS24)!
When: June 24-28, 2024
Where: Eindhoven, the Netherlands (@TUeindhoven, @Brainport_int)
Info: https://t.co/wtTLui2rBo
Application deadline: March 31, 2024
Don't wait, apply!

[Daniel Daza @danieldazac]

Our work on embedding multimodal biomedical knowledge graphs is now published at the Journal of Biomedical Semantics @BioMedCentral!
Read the paper here: https://t.co/IifHKrgFno

[Daniel Daza @danieldazac]

New preprint! We introduce BioBLP, a method for learning embeddings on multimodal knowledge graphs.

Paper: https://t.co/92TAkpOTRP
Code: https://t.co/deK9SlcO2L

w/ @DimitrisAlivas @pmitra01 @thompijn @michaelcochez @pgroth
1/4

[Taraneh Younesian @TYounesian]

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: https://t.co/S7vQOXT5eJ

[Daniel Daza @danieldazac]

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 https://t.co/FudDaZ2hAP
🍇 GRAPES: Scaling GNN training with GFlowNets
https://t.co/qnwHTqxKfv

Feel free to reach out!

[Jhony H. Giraldo @JhonyHGiraldo]

📢 Exciting news! We're presenting our paper "On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks" at @cikm2023 as a long paper (oral). Check out the preprint: https://t.co/XCLrN4Neos. The code is here: https://t.co/RqJVvxgUgc. 📚 #GNN

[Daniel Daza @danieldazac]

Thanks @BoXiongs, Mojtaba Nayyeri, @michaelcochez, I learned a lot from this experience!

Our slides are now online at https://t.co/yTyrjVTzr3

[Michael Cochez @michaelcochez]

With @danieldazac at #CIKM2023 giving a tutorial on Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings 🚀

[Daniel Daza @danieldazac]

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

[Conrad Godfrey @conradgodfrey]

GPT-4V "Describe this image"
🔃
Dall-E 3 "Generate this image"

Recursive loop

[Intelligent Data Engineering Lab @INDE_LAB_AMS]

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

[Daniel Daza @danieldazac]

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!

[Bo Xiong @BoXiongs]

Thrilled to announce that we will be giving a tutorial with @danieldazac @michaelcochez and Mojtaba on "Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings", at #cikm2023.

Slides will be available on the tutorial website https://t.co/hIrG0dwFpD. Stay tuned!