Taraneh Younesian
@TYounesianPhD researcher @vuamsterdam | Machine Learning | Knowledge Graphs
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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
Struggling with scaling RGCNs on large knowledge graphs? Check out "ReWise: A Relation-Wise Sampling Framework" by @TYounesian, @pbloemesquire, and Stefan Schlobach from @VUamsterdam now live at #SemanticsConf! Discover this game-changing approach for efficient RGCN training!
#GeMSS was a great experience! I learned a lot about Generative AI and met really cool people. Don't miss it next year!
This year, the fabulous @jmtomczak gave the closing remarks for our second #GenAI summer school (gemss.ai) and revealed that we are brining GeMSS to home of the fantastic @pamattei in Nice in 2025! #GeMSS
Attending #NeurIPS2023 this week? Interested in neurosymbolic reasoning or scaling GNNs to large graphs? Then, you might want to drop by our posters to learn about ⚡️ A-NESI and 🍇 GRAPES (@glfrontiers workshop) 1/4
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!
Great news! Our hybrid workshop on Neurosymbolic Generative Models was accepted at ICLR 2023🎉🎉🎉 More details on nesygems.github.io
SHAP, LIME, PFI, ... you can interpret ML models with many different methods. It's all fun and games until two methods disagree. What if LIME says X1 has a positive contribution, SHAP says negative? A thread about the disagreement problem, and how to approach it:
An interesting keynote by Mihaela van der Schaar @MihaelaVDS on interpretability and personalized explanations in UAI 2022! #UAI2022
The afternoon session started with Mihaela's keynote on "New frontiers in machine learning interpretability". Thanks for the inspiring talk!
Wanna work at the most exciting boundary in modern AI (combine machine learning and symbolic reasoning), and use it to improve drug safety for kidney patients, in a leading AI team, jointly with medical researchers? Apply for our PhD vacancy before 1 Sep! werkenbij.vu.nl/ad/phd-positio…
*Present Failures* ❌ "It doesn't work." ✅ "Here is HOW it fails. I feed X but somehow did not get Y. I believe the core issues lie in steps Z and W. I have ruled out W as the cause. Next, I will design experiments to isolate the step Z."
I want to talk about burnout. A brief 🧵... I was well aware I was burnt out in the fall, but it's hard to fully appreciate the impact of burnout in the moment. After 2 weeks of vacation and a month of aggressively blocking daily focus time, the impact has become more clear:
With some delay, I'm happy to announce that our paper "QActor: Active Learning on Noisy Labels" is accepted to ACML 2021! proceedings.mlr.press/v157/younesian… In this paper, we introduce an active learning-based method to relabel data with noisy labels in an efficient manner.
How to make steady progress in my research? I worked so damn hard but "IT JUST DOESN'T WORK!"😤 How can I unblock myself quickly and make good progress toward the goals? Below I compiled a list of tips that I found useful. 👇
Programming: 10% writing code. 90% figuring out why it doesn’t work Analyzing data and ML: 1% writing code. 9% figuring out why code doesn’t work. 90% figuring out what’s wrong with the data
Such a nice experience! Hope to see all these great people in person!
After 2 weeks of fun and learning, that's a wrap for #MLSS2020! Hope that everyone enjoyed it as much as we did (and that we get to meet soon-ish)! 🍻@Mj33567683 @arvanitg @wittawatj @bschoelkopf 🙌@TechAtBloomberg @AmazonScience @Bosch_AI @GoogleAI cc @MPI_IS @Cyber_Valley
#MLSS2020 made me realize how far I’ve got from my optimization/OR/and in general theoretical background, and how interesting these topics are for me! I’m planning to get back to my math roots thanks to the amazing talks in the summer school!
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