Estimating causal effects efficiently doesn’t have to mean discovering the entire causal graph! Now you can find the optimal adjustment from only local information using LOAD! 📜 Preprint: arxiv.org/abs/2510.14582 👾 Code: github.com/Matyasch/load 🧵 1/8

Carlos Cinelli, Avi Feller, Guido Imbens, Edward Kennedy, Sara Magliacane, Jose Zubizarreta Challenges in Statistics: A Dozen Challenges in Causality and Causal Inference https://arxiv.org/abs/2508.17099

Are you interested in improving the #interpretability, #robustness and #safety of current AI systems with #causality and #RL? Apply to our PhD position in Amsterdam 🚲🌷🇳🇱 Deadline: June 15

🔥 Got a great work on causal representation learning, abstraction, high-dimensional discovery, or other hot topics in causality? 🇧🇷 Don’t miss your chance to present in Rio at the CAR Workshop at #UAI2025! ⏰ Deadline is in 1 week – May 26! 🌐 sites.google.com/view/car-25/

A little over a week ago, I had the chance to attend #AISTATS and present our poster on SNAP (matyasch.github.io/snap)! Three days of brilliant invited talks and a stream of fascinating papers left me with a much longer reading list about ideas to explore.

New PhD position at the University of Amsterdam in @amlab.bsky.social on learning concepts with theoretical guarantees using #causality and #RL with me, Frans Oliehoek (TU Delft) and Herke van Hoof 💥 Deadline: 15 June werkenbij.uva.nl/en/vacancies...

Just arrived in Phuket for #AISTATS2025. Can't wait to present our poster (in tube) about SNAP 🫰 on day 2, Sunday! Come check it out and let's chat about scalable causal discovery!

⏰ Don't miss Mátyás talk today at 3PM! 🎥 See you online meet.google.com/cqt-ufji-xfz 🤌 ...or live in the CS Department of the University of Pisa!

A few weeks ago, I presented SNAP at the wonderful #Bellairs Workshop on Causality in Barbados🐢 This Friday 🫰meets 🤌 as I will get to present SNAP again at the kick-off of the newest season of @causalclub.di.unipi.it! Check out this, and their other amazing upcoming talks at causalclub.di.unipi.it

Do you want to estimate causal effects for a small set of target variables without knowing the causal graph, but discovering it takes too long? Now you can get adjustment sets in a SNAP🫰accepted at #aistats2025! 📜 arxiv.org/abs/2502.07857 🧩 matyasch.github.io/snap/ 🧵 1/10

Professor Imbens also had a mentoring session with our PhD students actively working on causality, discussing their ideas and the potential impact of their applications! 👨‍🔬👩‍🔬 @matyasch.bsky.social @roelhulsman.bsky.social @rmassidda.it @danruxu.bsky.social 🔥

Congrats to @smaglia.bsky.social for now being an ELLIS Scholar! 🤩🥳🎉

if you ever wondered how to concisely represent causal models, don’t miss my talk on causal abstraction tomorrow at @ellisamsterdam.bsky.social