uai2026

uai2026

@auai.org

Association for Uncertainty in AI. Upcoming conference: #uai2026 August 17-21 in Amsterdam, Netherlands! πŸ‡³πŸ‡± https://auai.org/uai2026

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Ready to bike along the canals? 🚲 The 42nd Conference on Uncertainty in AI will be in Amsterdam, August 17-21! πŸ‡³πŸ‡± CfP is out πŸ‘‰ auai.org/uai2026/call... 🚨 Feb 25: Paper submission πŸ—£οΈ Apr 23–May 2: rebuttal period πŸŽ‰πŸ’€ Jun 1: Author notification #UAI2026 #ML #stats #learning #reasoning #uncertainty #AI

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πŸ₯ˆ Runner-up: "Nonlinear Axiomatic Attribution for Cooperative Games" β€” Weida Li, Zhuanghua Liu, Yaoliang Yu, Bryan Kian Hsiang Low

πŸŽ–οΈ Honorable Mention: "Gaussian Process Limit Reveals Structural Benefits of Graph Transformers" β€” Nil Ayday, Lingchu Yang, Debarghya Ghoshdastidar

πŸ₯‡ Best Paper: "Fundamental Limits and Optimal Methods for Sharp Analytical Causal Bounds in Instrumental Variable Models" β€” Arefe Boushehrian, Mohammad Reza Badri, Sina Akbari, Negar Kiyavash

If you're still wondering whether you should join #UAI2026, think no more! The tutorials list is out, spanning probabilistic machine learning, interpretability, causality, LLM reasoning, constrained neural networks, and many more. πŸ‘‰ www.auai.org/uai2026/tuto...

🚨 Deadline extension! Don't miss the chance to introduce the #UAI2026 community to your work and research field! πŸ§‘β€πŸ« ⏳ Submit your proposal by the end of May 8th (AoE) πŸ‘‰ auai.org/uai2026/call...

🚨 The deadline for our Call for Tutorials is approaching. Don't miss the chance to introduce the #UAI2026 community to your work and research field! πŸ§‘β€πŸ« ⏳ Submit your proposal by the end of April 30th (AoE) πŸ‘‰ auai.org/uai2026/call...

πŸŽ‰ We’re excited to announce the Keynote Speakers for #UAI2026 β€” three researchers shaping the future of causal learning, large-scale ML, and responsible AI. πŸ‘‡

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@lestermackey.bsky.social (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.

Julia Stoyanovich (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 β€” advancing accountability alongside innovation.

πŸŽ‰ We’re excited to announce the Keynote Speakers for #UAI2026 β€” three researchers shaping the future of causal learning, large-scale ML, and responsible AI. πŸ‘‡

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.

Get your OpenReview account ready: submissions open in two weeks! πŸ“ πŸ“… Submissions open: Jan 25, 2026 🚨 Submission deadline: Feb 25, 2026 See you in Amsterdam! πŸ‡³πŸ‡±πŸš² πŸ‘‰ auai.org/uai2026/call... #UAI2026 #ML #Statistics #Learning #Reasoning #Uncertainty #AI

uai2026 reposted

then on The Workshop on Causal Abstractions and Representations #CAR25 sites.google.com/view/car-25/

uai2026@auai.org

memories from the last day of #UAI2025: the 8th Workshop on Tractable Probabilistic Modeling #TPM2025 tractable-probabilistic-modeling.github.io/tpm2025/

and "Modern Approximate Inference: Variational Methods and Beyond" by Diana Cai (Flatiron Institute) and Yingzhen Li (Imperial College London)

uai2026@auai.org

2) "Causal Inference with Deep Learning and Generative Models" by Murat Kocaoglu (Purdue University) and Md Musfiqur Rahman (Purdue University)

2) "Causal Inference with Deep Learning and Generative Models" by Murat Kocaoglu (Purdue University) and Md Musfiqur Rahman (Purdue University)

uai2026@auai.org

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)