UAI

ML/AI Core

1,698 papers · 2019–2026

UAI (Conference on Uncertainty in Artificial Intelligence) focuses on probabilistic modeling, reasoning under uncertainty, and causal inference.

Papers per year

119

140

206

230

243

201

229

330

'20

'25

Top authors

Eyke Hüllermeier 14 papers

Ilya Shpitser 13 papers

Vahid Tarokh 11 papers

Joris M. Mooij 11 papers

Sanghack Lee 11 papers

Bernhard Schölkopf 10 papers

Negar Kiyavash 10 papers

Ping Li 10 papers

Kristian Kersting 9 papers

Samuel Kaski 9 papers

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their counts at this venue are combined. How identity is handled.

Newest papers

Learning Lineage-guided Geodesics with Finsler Geometry 2026

Towards Identifiability of Interventional Stochastic Differential Equations 2026

Revisiting TD Target Aggregation under Uncertainty in Q-Learning 2026

Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings 2026

Unified Confidence Adjustment for Robust Cross-Modal Retrieval under Test-Time Distribution Shifts 2026

Bandwidth Selection in Kernel Density Estimation for Model Calibration 2026

Uncertainty Quantification of Click and Conversion Estimates for the Autobidding 2026

Self-Supervised Uncertainty Estimation For Super-Resolution of Satellite Images 2026

SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory 2026

Efficient Decentralized Learning of Generalized Quantal Response Equilibrium 2026

Gungnir: Exploiting Stylistic Features in Images for Backdoor Attacks on Diffusion Models 2026

Instrumental and Proximal Causal Inference with Gaussian Processes 2026

Not All Queries Need Deep Thought: CoFiCot for Adaptive Coarse-to-fine Stateful Refinement 2026

FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching 2026

Interpretable Causal Discovery via Causal-Effect Constraints 2026

Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness 2026

ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis 2026

Structural Drift Repair in Decision Trees via Bayesian Model-Based Diagnosis 2026

A Debiased LASSO Estimator for Design Matrices with Non-zero Mean Elements 2026

On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference 2026

All UAI 2026 papers →