Prediction is useful. Understanding *why* things happen is powerful. Causal machine learning helps move beyond correlation to real insight, supporting smarter, more ethical decisions across industries. #CausalML #MachineLearning #DataScience #ExplainableAI #DecisionScience

Avik Basu - Beyond Just Prediction: Causal Thinking in Machine Learning | PyData Seattle 2025 #machinelearning #correlation #causality #uplift #metalearner #slearner #tlearner #xlearner #causalml #scikituplift #econml

Excited to share our new paper in Psychological Methods: “Machine Learning for Propensity Score Estimation: A Systematic Review and Reporting Guidelines.” Led by Prof. Walter Leite (UF) with 6 co-authors across 6 universities. DOI: doi.org/10.1037/met0...
#CausalML #PropensityScore

AI Framework Enhances Causal Machine Learning for Surgical Treatment Effects

New AI framework X-MultiTask achieves a top AUC of 0.84 for anterior spinal-fusion and 0.77 for posterior, with lowest ε_nn-PEHE of 0.2778. Read more: getnews.me/ai-framework-enhances-ca... #causalml #surgery

Excited to join the Impact 25 workshop at #EurIPS2025 in Copenhagen, Dec 6–7! 🌍✨

We'll explore how to boost the real-world impact of causal ML, representation learning, discovery & inference across health, social & earth sciences.

👉 impact-25.causal.dev
#CausalInference #CausalML #Impact25

Causal-Symbolic Meta-Learning Enables Few-Shot Causal Reasoning

The new Causal‑Symbolic Meta‑Learning (CSML) framework learns causal graphs from few examples and outperformed baselines on the CausalWorld benchmark. Read more: getnews.me/causal-symbolic-meta-lea... #causalml #meta-learning

Postdoctoral Position- UC Davis Graduate School of Management University of California, Davis is hiring. Apply now!

🚨 Hiring a postdoc @ucdavis.bsky.social‬ GSM!
Work on causal inference + econometrics + ML:
- Heterogeneous effects
- Dynamic interventions
- Censoring & noncompliance
Strong stats theory + R/Python
Start: Fall 2025
Apply → recruit.ucdavis.edu/JPF07156
#CausalML #EconSky #PostdocJobs

Causal machine learning for assessing the effectiveness of off-label use of amiodarone in new-onset atrial fibrillation
Feuerriegel, S., Ghanbari, H. et al.
Paper
Details
#CausalML #OffLabelAmiodarone #AFibTreatment

Grateful to present recent research @SFU International Conference in Statistics & Data Science 2025 Simon Fraser University in Vancouver on #TargetTrialEmulation using electronic health records to estimate average treatment effects & #CausalML conditional average treatment effects

🚨 Call for Papers: Causal Data Science Meeting 2025
📅 November 12–13, 2025 (Virtual)

📥 Submit by Sept 30: submission@causalscience.org
🎙️ Keynote: Stefan Feuerriegel (LMU Munich)

🌐 More Info and registration: causalscience.org
#CausalML #AI #DataScience #CDSM2025 #CanIPetThatDAG

The OutcomeWeights #RStats package now has a logo and a new vignette illustrating how Double ML improves covariate balance over "Single ML" RA or IPW.

Check it out:
mcknaus.github.io/OutcomeWeigh...

#causalSky #causalML

One year ago I gave a #CausalML Workshop for Ukraine 🇺🇦
We hand-coded DoubleML and causal forest in very few lines of code to exactly replicate their package outputs.
If you better understand theory through coding like me, check it out.
You find the R notebook now online: shorturl.at/uM82n
#RStats

I think people are waiting for clear proof that #Causal ML will do better on real world problems. Right now everyone uses supervised ML and ignores confounding. I’m working on a project at my company to try #CausalML. High memory usage for large datasets is a problem for CML

🔍 Causal ML for Predicting Treatment Outcomes
📅 March 12 | 🕓 16:00h
🎙️ By Valentyn Melnychuk

Join us to explore how causal machine learning helps predict treatment effects with real-world impact! 🚀

#CausalML #MachineLearning #AI

Maybe. But there really are some valuable things in this wave. And not all the things people think. I’m personally more excited about #CausalML than #LLM! No one knows about CML but it will be remembered as a product of this wave.

Sample Efficient Bayesian Learning of Causal Graphs from Interventions Causal discovery is a fundamental problem with applications spanning various areas in science and engineering. It is well understood that solely using observational data, one can only orient the...

We will present this work at #NeurIPS2024 on Wednesday at 4:30pm local time in Vancouver. Poster #5107.

Led by my PhD students Zihan Zhou and Qasim Elahi.

Paper link:
openreview.net/forum?id=RfS...

Follow us for more updates from the #CausalML Lab!

Partial Structure Discovery is Sufficient for No-regret Learning in... Causal knowledge about the relationships among decision variables and a reward variable in a bandit setting can accelerate the learning of an optimal decision. Current works often assume the causal...

I will present this work at #NeurIPS2024 next Thursday at 11am local time in Vancouver. Poster #5104.

Led by my PhD student Qasim Elahi. Joint work with my colleague Mahsa Ghasemi.

Paper link:
openreview.net/forum?id=uM3...

Follow us for more updates from the #CausalML Lab!

Conditional Generative Models are Sufficient to Sample from Any... Causal inference from observational data plays critical role in many applications in trustworthy machine learning. While sound and complete algorithms exist to compute causal effects, many of them...

We will present this work at #NeurIPS2024 next Thursday at 11am local time in Vancouver. Poster #5103.

Joint work led by my PhD student
Md. Musfiqur Rahman and colleague Matt Jordan.

Paper link:
openreview.net/forum?id=vym...

Follow us for more updates from the #CausalML Lab!

The Uncertainty in Artificial Intelligence conference (UAI) is on 🦋!

I'm a bit biased, but this is a fantastic conference for #probabilisticML, #causality, #causalML, #tractable #probabilistic #models, #imprecise probabilities,
#reasoning, #neurosymbolic approaches and more.

#causalSky #statSky

#CausalML update - fitting my first #CausalForest on real data! Does anyone have advice on the most important #hyperparameters? I've got large imbalanced data and a lot of treatment variables, so it's not like anything you see in the economics literature. 🤔 #ML #AI #causal #dataskyence

We’ll be presenting it as a poster in Vancouver on December 11th! 🌟

💡 Meanwhile, check out our interactive demo: gulnazaki.github.io/counterfactu...

📄 Read our paper: arxiv.org/abs/2403.20287

Excited to share this work at NeurIPS 2024! 🚀

#Counterfactuals #NeurIPS #Benchmarking #CausalML

Join (or enable others to join) my gentle intro to #CausalML next Thursday (11.4.). A 2h ride from OLS to Double ML to Causal Forests only using few lines of R code.
It is going to be fun 😀

If you have questions, feel free to reach out to us: either via dm or email to trainings@economicai.com #doubleml #causalml #causalai #ai #machinelearning #pricing #marketing #abtesting #experimentation #upliftmodelling #personalization

Are causal models probabilistic programs?

ChiRho has an answer.

#causalsky #causalml #python #machinelearning

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