Postdoc at Amsterdam UMC, working on machine learning and graphs.
Amsterdam, The Netherlands
Joined February 2016
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- Following312
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Daniel Daza retweeted
🚀 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=183X… @LogConference
Daniel Daza retweeted
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: ebooks.iospress.nl/doi/10.32…
Daniel Daza retweeted
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
Daniel Daza retweeted
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: gemss.ai/
Application deadline: March 31, 2024
Don't wait, apply!
Daniel Daza retweeted
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
Daniel Daza retweeted
📢 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: arxiv.org/abs/2212.02374. The code is here: github.com/jhonygiraldo/SJLR. 📚 #GNN
Daniel Daza retweeted
In this exciting call, we also have an opening for an assistant professor in data engineering. Check it out.
This Post is from an account that no longer exists. Learn more
Daniel Daza retweeted
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: arxiv.org/abs/2301.12313
Daniel Daza retweeted
📚 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-mac…
Daniel Daza retweeted
The neural query answering crowd of @michaelcochez, @DimitrisAlivas, @_kire_kara_ , @BerrendorfMax, @danieldazac, @PMinervini, @Mniepert, @ren_hongyu, (and yours truly) contributed Chapter 17 about Approximate Answering of Graph Queries to this monumental book. Check it out!
The new edited book
Compendium of Neurosymbolic Artificial Intelligence
is now available - 30 chapters (700 pages), each conveying integrated content from several published papers of recent years.
iospress.com/catalog/books/c…
Daniel Daza retweeted
The new edited book
Compendium of Neurosymbolic Artificial Intelligence
is now available - 30 chapters (700 pages), each conveying integrated content from several published papers of recent years.
iospress.com/catalog/books/c…
Daniel Daza retweeted
I collected all my writing on PCA into a free long-form math book.
peterbloem.nl/publications/u…
It's called "Unraveling principal component analysis" and it contains a narrative explanation of PCA all the way down to the foundations.
I discuss eigenvectors, SVD and much more.
ALT Cover of a book called "Unraveling principal component analysis".
ALT A diagram illustrating the eigendecomposition.
ALT A diagram illustrating how a mirror turns you front-to-back rather than left-to-right.
ALT A diagram illustrating a rank decomposition.
Daniel Daza retweeted
We are organizing a challenge on knowledge base construction with LLMs at this year's @iswc_conf.
Submit your method and join our interesting discussions about knowledge graphs and language models.
LM-KBC challenge happens again at ISWC'2023!
Submit your strongest LM-based knowledge base construction methods until August 2.
lm-kbc.github.io/challenge20…
Daniel Daza retweeted
Do #BERT-based entity retrieval models benefit from additional entity information stored in knowledge graphs?
Join us at ✨Search Engines Amsterdam Talk (hybrid) ✨ w/Emma Gerritse (Radboud Univ.) & Ridho Reinanda (Bloomberg) on Fri, 24 Feb at 5PM CET
meetup.com/nl-NL/sea-search-…
Daniel Daza retweeted
Very happy for @melikaayoughi Her new paper "Self-Contained Entity Discovery from Captioned Videos" is published in ACM TOMM. Great collaboration with @PascalMettes . I learned a lot. Great @UvA_IvI team work VIS Lab + @INDE_LAB_AMS cc @cgmsnoek
dl.acm.org/doi/10.1145/35831…
Daniel Daza retweeted
🎄It's 2023! In a new post, we provide an overview of Graph ML and its subfields (and hypothesize for '23), eg Generative Models, Physics, PDEs, Theory, KGs, Algorithmic Reasoning, and more!
With @ren_hongyu @zhu_zhaocheng @chrsmrrs and @jo_brandstetter
mgalkin.medium.com/graph-ml-…
Daniel Daza retweeted
We are hiring! Assistant Professor in #DataEngineering. Come join us and the be part of the amazing Amsterdam data + AI ecosystem @UvA_IvI @AITech_UvA @uva_dsc vacatures.uva.nl/UvA/job/Ass…
Daniel Daza retweeted
We are live! Investigating and deploying human centred explanations for AI systems combining machine learning and knowledge graphs @unipb @UvA_Amsterdam @NCSR_Demokritos @DATEV @eusatcen @webLyzard
Funded by @HorizonEU. More:
uni-paderborn.de/en/news-ite…
Daniel Daza retweeted
💥KG Embedding Models are GNNs! 💥 We found that their training dynamics can be described via message-passing operations, enabling us to define a new type of GNNs that achieves SOTA results on inductive and transductive link prediction tasks! #NeurIPS22 arxiv.org/abs/2207.09980 🧵
Daniel Daza retweeted
LoG 2022 will be free to attend! Registration is now open👇
🤖 Registrations are now open for the first Learning on Graphs Conference.
LoG is virtual from 9th - 12th December 2022 and completely FREE to attend!
Sign up now for the latest research and applications in machine learning for graphs and geometry:
eventbrite.com/e/learning-on…
