LCA on Graphs @LCAonGraphs
Knowledge Graphs and Graph Machine Learning for quantitative sustainable assessments Amsterdam Joined December 2020-
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Fun to think about open-source models and their variants as families from an evolutionary biology standpoint and analyze "genetic similarity and mutation of traits over model families". These are the 2,500th, 250th, 50th and 25th largest families on @huggingface:
Fun to think about open-source models and their variants as families from an evolutionary biology standpoint and analyze "genetic similarity and mutation of traits over model families". These are the 2,500th, 250th, 50th and 25th largest families on @huggingface: https://t.co/1RSlkq0EfF
Huge computer science result: A Tsinghua professor JUST discovered the fastest shortest path algorithm for graphs in 40yrs. This improves on Turing award winner Tarjan’s O(m + nlogn) with Dijkstra’s, something every Computer Science student learns in college.
Our open models are here. Both of them. openai.com/open-models
Today, we're introducing AlphaEarth Foundations from @GoogleDeepMind , an AI model that functions like a virtual satellite which helps scientists make informed decisions on critical issues like food security, deforestation, and water resources. AlphaEarth Foundations provides a…
iText2KG: an open source Python package designed to incrementally construct consistent knowledge graphs with resolved entities and relations iText2KG v0.0.8 is out, and it can now build dynamic knowledge graphs. iText2KG is a Python package designed to incrementally construct…
This will be great newgraphperspectives.com.
Building Knowledge Graphs with LLM Graph Transformer #GNN medium.com/data-science/b…
Graph Transformers: From Message Passing to Global Attention Deep learning’s most spectacular successes share the same secret ingredient: an architecture that respects the geometric structure of the data. CNNs thrive because images are grids; LSTMs succeeded at language because…
Physicists and mathematicians really have the wriest humor.
Check out this blogpost from @ffabffrasca and the GLOW reading group on the future of graph learning! I’ve also contributed and my main take is - its actually working and its an exciting moment to work on applications!
Since a few days, @GeminiApp keeps getting it wrong with imported spreadsheet from my drive, leading to inaccurate retrievals of items. It used to work like a charm! What changed? 🤔
📣 Our spicy ICML 2025 position paper: “Graph Learning Will Lose Relevance Due To Poor Benchmarks”. Graph learning is less trendy in the ML world than it was in 2020-2022. We believe the problem is in poor benchmarks that hold the field back - and suggest ways to fix it! 🧵1/10
If you're working with LLMs and struggling to get accurate results from structured or private data, this session is for you: zoom.us/webinar/regist…
🚀 The future of #AI is human–AI collaboration! Our new paper explores how integrating #LLMs with Human-in-the-Loop greatly enhances #KnowledgeGraph generation and validation. We present several innovative strategies to minimise manual effort. 📄 doi.org/10.1016/j.ipm.… #HitL
📣Two new blog posts - a comprehensive review of Graph and Geometric ML in 2023 with predictions for 2024. Together with @mmbronstein, we asked 30 academic and industrial experts about the most important things happened in their areas and open challenges to be solved. 🧵 1/n
i have been experimenting with google gemini writing visual solutions to math problems using @manim_community some light bugs but it's getting there..
I'm falling in love with @GeminiApp 2.5 !!! So much potential 🤩 (even though there are still some bugs 😅)
LLMs exhibit the Reversal Curse, a basic generalization failure where they struggle to learn reversible factual associations (e.g., "A is B" -> "B is A"). But why? Our new work uncovers that it's a symptom of the long-standing binding problem in AI, and shows that a model design…
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EurIPS Conference @EurIPSConf
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