Uncertainty in Artificial Intelligence (UAI)
41st Conference on Uncertainty in Artificial Intelligence
Rio de Janeiro, Brazil
July 21-25, 2025
Link: https://www.auai.org/uai2025/
The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. UAI is supported by the Association for Uncertainty in Artificial Intelligence (AUAI).
Important Dates
Name | Date |
|---|---|
| Paper submission deadline (incl. supp. material) | February 10th, 2025 (23:59 Anywhere on Earth, AoE) |
| Author response/discussion period | April 3rd - April 10th, 2025 (23:59 AoE) |
| Author notification | May 6th, 2025 (23:59 AoE) |
| Camera-ready deadline | June 6th, 2025 (23:59 AoE) |
Subject Areas
Below you find a non-exhaustive list of relevant topics for your reference.
Algorithms
- Approximate Inference
- Bayesian Methods
- Belief Propagation
- Exact Inference
- Kernel Methods
- Missing Data Handling
- Monte Carlo Methods
- Optimization - Combinatorial
- Optimization - Convex
- Optimization - Discrete
- Optimization - Non-Convex
- Probabilistic Programming
- Randomized Algorithms
- Spectral Methods
- Variational Methods
Applications
- Cognitive Science
- Computational Biology
- Computer Vision
- Crowdsourcing
- Earth System Science
- Education
- Forensic Science
- Healthcare
- Natural Language Processing
- Neuroscience
- Planning and Control
- Privacy and Security
- Robotics
- Social Good
- Sustainability and Climate Science
- Text and Web Data
Learning
- Active Learning
- Adversarial Learning
- Causal Learning
- Classification
- Clustering
- Compressed Sensing and Dictionary Learning
- Deep Learning
- Density Estimation
- Dimensionality Reduction
- Ensemble Learning
- Feature Selection
- Hashing and Encoding
- Multitask and Transfer Learning
- Online and Anytime Learning
- Policy Optimization and Policy Learning
- Ranking
- Reinforcement Learning and Bandits
- Relational Learning
- Representation Learning
- Semi-Supervised Learning
- Structure Learning
- Structured Prediction
- Unsupervised Learning
Models
- Foundation Models
- Generative Models
- Graphical Models
- Models for Relational Data
- Neural Networks
- Probabilistic Circuits
- Regression Models
- Spatial, Temporal and Spatio-Temporal Models
- Topic Models and Latent Variable Models
Principles
- Causality
- Computational and Statistical Trade-Offs
- Explainability
- Fairness
- Privacy
- Reliability
- Robustness
- (Structured) Sparsity
Representation
- Constraints
- Dempster-Shafer
- (Description) Logics
- Imprecise Probabilities
- Influence Diagrams
- Knowledge Representation Languages
Theory
- Computational Complexity
- Control Theory
- Decision Theory
- Game Theory
- Information Theory
- Learning Theory
- Probability Theory
- Statistical Theory
Dec 18, 2024 at 11:16 AM