12/10 産研テクノサロン 企業DXを加速する因果AIの最前線 sanken.osaka-u.ac.jp/labs/air/techn… 清水昌平 (阪大) 因果AIへの招待 泉谷知範・藤原大悟（NTTドコモビジネス) 製造業を中心としたIoTデータのための因果分析の実際 高木拓也（富士通）データドリブンな意思決定に向けた統計的因果探索技術とその活用事例

Hiring postdoc UC San Diego! Join our Causal Intelligence Lab (PI: Biwei Huang) to work on causality-driven world models, VLA, and RL for embodied AI.

I will be at #NeurIPS2025 next week. If you are also curious about the hidden world behind observational data (e.g., trustworthy ML, causal representation learning, latent-space reasoning/collaboration), let's chat! PS: I'm currently on the academic job market. Happy to connect

📝 Paper submissions for #CLeaR2026, which will be held on April 6-8 at the Broad Institute, are due December 15. CLeaR brings together researchers advancing causal discovery, inference, and the role of causality in modern ML. Learn more and submit: cclear.cc/2026/CallforPa…

The deadline for submissions to the 5th Conference on Causal Learning and Reasoning (CLeaR) has been extended to December 22nd, AOE. Please submit your best work on causality! cclear.cc/2026/CallforPa…

Ready to bike along the canals? 🚲 The 42nd Conference on Uncertainty in AI will be in Amsterdam, August 17–21! 🇳🇱 CfP here 👉 auai.org/uai2026/call_f… 🚨 Feb 25 deadline 🗣️ Apr 23–May 2 rebuttal 🎉💀 Jun 1 notification #UAI2026 #ML #stats #learning #reasoning #uncertainty #AI

Meta × TBD Lab × CMU × UChicago × UMaryland In our latest work, we introduce Token-Level LLM Collaboration via FusionRoute 📝: arxiv.org/pdf/2601.05106 LLMs have come a long way, but we continue to face the same trade-off: – one huge model that kind of does everything, but is

Added a short thread with key ideas and intuition about diverse dictionary learning below ↓