Erkan Karabulut @erkankarabulut.bsky.social · 23/08/2026Time is a resource that you can spend on your to-do list to have big numbers in life. A balanced to-do list contains many leisure (maintenance) times scheduled tightly with everything else. The total (big) number of events, leisure or not, is to be optimized. Religiously healthy human. Sarcasm. 000
Erkan Karabulut @erkankarabulut.bsky.social · 03/07/2026PyAerial can now do much faster knowledge discovery from tabular data via rule learning with a tree-based rule extractor (v1.1)! If you are interested in knowledge discovery or interpretable machine learning for high-stakes decision making, check out PyAerial. github.com/DiTEC-projec...github.comGitHub - DiTEC-project/pyaerial: Scalable association rule mining from tabular datasets.Scalable association rule mining from tabular datasets. - DiTEC-project/pyaerial 100
Erkan Karabulut @erkankarabulut.bsky.social · 30/04/2026#IJCAI2026, #ECAI2026 decisions are out. Despite having written a rebuttal in hard personal circumstances, receiving no response to our rebuttal from reviewers, SPCs, ACs, or PCs is really heartbreaking. 000
Erkan Karabulut @erkankarabulut.bsky.social · 19/02/2026Tabular foundation models can learn association rules out of the box! For the non-expert: If you work with tables and want to discover interesting patterns, tabular foundation models (TFMs) can quickly find significant, interesting, and generalizable patterns with no additional training. 🧵1/7 101
Reposted by Erkan KarabulutBJGP @bjgp.org · 26/01/2026No. 2 #BJGPTop10 AI in lung cancer detection: AI algorithm identifies risk of lung cancer 4 months earlier doi.org/10.3399/BJGP... #LungCancer #CancerResearch #AIHealthcare #DigitalHealth #EarlyDetection #MedicalInnovation #ArtificialIntelligence #PrimaryCare #BJGP #research 012
Reposted by Erkan KarabulutMadelon Hulsebos @madelonhulsebos.bsky.social · 22/01/2026Join the TRL Seminar tomorrow for talks on query ambiguity in open-domain data analysis @daniel-gomm.bsky.social, the SQaLE dataset for training text-to-SQL models @cowolff.bsky.social, and pattern/rule inference from tabular data @erkankarabulut.bsky.social. Info: trl-lab.github.io/trl-seminar/trl-lab.github.io TRL Seminar | TRL Lab 153
Erkan Karabulut @erkankarabulut.bsky.social · 14/11/2025PyAerial documentation is now much more comprehensive and has a lot of examples: pyaerial.readthedocs.io/en/latest/in... If you are interested in interpretable machine learning or knowledge discovery, check out PyAerial! 000
Erkan Karabulut @erkankarabulut.bsky.social · 12/11/2025Yesterday, I gave a seminar on Scalable Knowledge Discovery with Neurosymbolic Rule Learning at the University of Amsterdam’s Data Science Center. Here’s a blog post with code samples and experiments on knowledge discovery from tabular data: 📄 erkankarabulut.github.io/blog/uva-dsc....erkankarabulut.github.ioUvA Data Science Center Seminar: Scalable Knowledge DiscoveryA walkthrough of scalable knowledge discovery from tabular data using neurosymbolic methods, covering association rule mining, its challenges, and neurosymbolic solutions with Aerial. 000
Erkan Karabulut @erkankarabulut.bsky.social · 26/10/2025Why is defining consciousness not trivial? I am attending the ECAI2025 workshop ACAI - Awakening Consciousness in Artificial Intelligence. And hearing different sound and consistent, at first, definitions or assumptions around consciousness made me think of this question. 110
Erkan Karabulut @erkankarabulut.bsky.social · 22/10/2025I'm excited to present our new method for enhancing knowledge discovery from tabular data using tabular foundation models at the #ECAI2025 conference workshops (ANSyA) this Sunday, October 26th. See our paper, Discovering Association Rules in High-Dimensional Small Tabular Data, below 👇. 🧵1/2 111
Erkan Karabulut @erkankarabulut.bsky.social · 26/09/2025Tabular foundation models can boost knowledge discovery from high-dimensional tabular data with few instances (e.g., gene expression or rare disease data, 1K+ columns and <100 rows)! 📄 Short Paper (Accepted at ECAI 2025 workshops, ANSyA): arxiv.org/pdf/2509.20113 🐍 Code: tinyurl.com/3z8cmuhw 🧵1/8lnkd.inLinkedInThis link will take you to a page that’s not on LinkedIn 131
Erkan Karabulut @erkankarabulut.bsky.social · 14/09/2025New software paper published in the SoftwareX journal, describing our neurosymbolic scalable association rule learner PyAerial for knowledge discovery and interpretable inference! 🔎 See the practical implications, capabilities, and benchmarking below! 📜 lnkd.in/eQubA7MD 🐍 lnkd.in/eDWnVWFr 🧵1/8 110
Erkan Karabulut @erkankarabulut.bsky.social · 07/09/2025I will be at the NeSy2025 conference this week, presenting Aerial scalable neurosymbolic tabular rule learner! Feel free to reach out if you are interested in knowledge discovery, interpretable inference! 110
Erkan Karabulut @erkankarabulut.bsky.social · 15/08/2025PyAerial looks much nicer now, with new CI/CD implemented, 50+ test cases and visualizations of association rules! Learning rules over large tables for knowledge discovery and interpretable inference is much easier with PyAerial. github.com/DiTEC-projec...github.comGitHub - DiTEC-project/pyaerial: A Python package of the Aerial neurosymbolic association rule mining algorithm from tabular datasets.A Python package of the Aerial neurosymbolic association rule mining algorithm from tabular datasets. - DiTEC-project/pyaerial 000
Erkan Karabulut @erkankarabulut.bsky.social · 30/07/2025I wrote a new blog post that introduce our new neurosymbolic tabular rule learner (accepted at NeSy 2025) in an intuitive level. Feel free to reach out if you wanna discuss about it! 📄 erkankarabulut.github.io/blog/scalabl...erkankarabulut.github.io 030
Erkan Karabulut @erkankarabulut.bsky.social · 23/07/2025Rule learning is valuable but overlooked in modern AI; we argue it merits more focus for two reasons: knowledge discovery and interpretable inference. Our NeSy 2025 paper presents a state-of-the-art neurosymbolic tabular rule learner. 📄 arxiv.org/pdf/2504.19354 🐍 github.com/DiTEC-projec... 🧵1/8arxiv.org 131
Erkan Karabulut @erkankarabulut.bsky.social · 04/05/2025New Python package for scalable association rule mining! We propose a novel neurosymbolic method for scalable rule mining from tabular data that can be used for both knowledge discovery and fully interpretable inference. 🧩 github.com/DiTEC-projec... 📜 arxiv.org/pdf/2504.19354 🧵1/5 162
Erkan Karabulut @erkankarabulut.bsky.social · 14/04/2025On Wednesday (16th of April) at the NWO ICT.Open, I will present our work on Interpretable Decision-Making in (Digital Twins of) Smart Environments for high-stakes decision-making. If you are interested, please visit me on the exhibition floor! See the details below 👇 100
Erkan Karabulut @erkankarabulut.bsky.social · 06/04/2025There are only so many words and actions we can say or do, and they are no match for the complexity of what's going on in our brain. Whatever anyone says or does, it is not exactly what they meant to say or do. It's just a misalignment of computation and memory to output. 010
Erkan Karabulut @erkankarabulut.bsky.social · 09/03/2025There is something inhuman in quantifying and optimizing things that I can not pinpoint. It is not only that we miss-quantity the unquantifiable or misrepresent the intangible to pursue as goals, but deeper. It is depressing to think every human institution rests on quantification and optimization. 011
Reposted by Erkan KarabulutThiviyan Thanapalasingam @thiviyan.bsky.social · 20/12/2024Together with @kareemyousrii.bsky.social, we announce the Neurosymbolic Generative Models special track at the NeSy 2025 Conference 🎉 Call for Papers is live! 2025.nesyconf.org/nesy-generat... See you in Santa Cruz in Sep 2025! @nesyconf.org2025.nesyconf.orgNeurosymbolic Generative Models19th International Conference on Neurosymbolic Learning and Reasoning (NeSy 2025, 8-10 September 2025, Santa Cruz, CA, USA) 0289
Erkan Karabulut @erkankarabulut.bsky.social · 24/11/2024Hello Bluesky! I am a researcher focusing on neurosymbolic knowledge discovery and decision-making in smart environments. 010