🥇 Best Paper: "Fundamental Limits and Optimal Methods for Sharp Analytical Causal Bounds in Instrumental Variable Models" — Arefe Boushehrian, Mohammad Reza Badri, Sina Akbari, Negar Kiyavash
@stoyanoj (NYU) leads the Center for Responsible AI and works to make "responsible AI" synonymous with "AI". Her research spans data systems, AI governance, and public policy — advancing accountability alongside innovation.
@LesterMackey (MSR) develops machine learning theory and methods for large-scale, high-impact applications in climate science, healthcare, and social good. MacArthur Fellow and 2025 COPSS Presidents’ Award recipient, with award-winning work across NeurIPS, ICML, and beyond.
Julie Josse (Inria) leads the PreMeDICaL team with Inserm. She works on advances personalized medicine through causal learning and privacy-preserving federated methods to accelerate targeted therapies and decision-support tools with quantified uncertainty.
congratulations to Paula Cordero Encinar, Francesca Romana Crucinio and O. Deniz Akyildiz (@odakyildiz) for winning the 🏆 Best Student Paper Award 🏆 at #UAI2025 with
"Proximal Interacting Particle Langevin Algorithms"
👉 openreview.net/forum?id=rTqy…
congratulations to Frédéric Koriche, Jean-Marie Lagniez and Chi Tran for winning the 🏆 Best Paper Award 🏆 at #UAI2025 for
"Probabilistic Explanations for Regression Models"
👉 openreview.net/forum?id=ipnY…
we open day 3 with Elias Bareinboim (@eliasbareinboim ) giving a keynote on
"Towards Causal Artificial Intelligence"
reprising some of the themes of his upcoming book (causalai-book.net/)
and
"Modern Approximate Inference: Variational Methods and Beyond"
by Diana Cai @dianarycai (Flatiron Institute) and Yingzhen Li @liyzhen2 (Imperial College London)
we reprise our Day 1 schedule with three amazing tutorials:
1) "Introduction to Bayesian Nonparametric Methods for Causal Inference"
by Michael Daniels (U of Florida) and Jason Roy (Rutgers)
we reprise our Day 1 schedule with three amazing tutorials:
1) "Introduction to Bayesian Nonparametric Methods for Causal Inference"
by Michael Daniels (U of Florida) and Jason Roy (Rutgers)
time for our mentoring session!
where young researchers can ask more experienced ones about how to navigate academia, conferences, work in industry and more!
Moderated by Eli Carrami and Isabela Albuquerque (virtual)
Panel: Cassio de Campos @sabinasloman@liyzhen2
Welcome to Rio 🇧🇷!
While we start, enjoy the sun, our local coffee swag ☕ and our upcoming five tutorials for the day (auai.org/uai2025/tutorials) 💙
stay tuned!
Welcome to Rio 🇧🇷!
While we start, enjoy the sun, our local coffee swag ☕ and our upcoming five tutorials for the day (auai.org/uai2025/tutorials) 💙
stay tuned!
next is Elias Bareinboim (@eliasbareinboim) from Columbia University, who will discuss in his keynote talk about the recent
✨ progress toward building causally intelligent AI systems ✨
full abstract 👉 auai.org/uai2025/keynote_spe…
time to announce our amazing keynote speakers!
we start with Francesca Dominici (@francescadomin8) from Harvard University, who will talk about:
✨ AI's uncertain, double-edged role in the fight against climate change ✨
full abstract 👉 auai.org/uai2025/keynote_spe…
time to announce our amazing keynote speakers!
we start with Francesca Dominici (@francescadomin8) from Harvard University, who will talk about:
✨ AI's uncertain, double-edged role in the fight against climate change ✨
full abstract 👉 auai.org/uai2025/keynote_spe…
Early bird registration deadline is next Monday 2nd of June 🏃♂️
you can register to attend in person or as virtual participants!
⚡ auai.org/uai2025/registratio… ⚡
what a great initiative for #AI , well done @Khipu_AI!
and what a year for Latin America! In fact, also #UAI is in South America, and specifically in Rio 🇧🇷!
See you there!
Devendra Singh Dhami @devendratweetin is talking about probabilistic circuits for causal inference in the 7th Workshop on Tractable Probabilistic Modeling.
Our first oral session on deep learning featured five talks on Bayesian deep learning, generative models, visual concept learning and regression with heteroskedastic noise.
If you can’t wait til the break for your morning coffee, check out the cafeteria across the yard in the building right across the entrance. And with super affordable prices!