UAI 2021 : Conference on Uncertainty in Artificial Intelligence (UAI)

in Conferences   Posted on November 23, 2020 

Conference Information

Submission Deadline Friday 19 Feb 2021 Proceedings indexed by :
Conference Dates Jul 26, 2021 - Jul 30, 2021
Conference Address Online, Online
Conference & Submission Link https://auai.org/uai2021/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Impact Score 3.63
#Contributing Top Scientists 38
#Papers published by Top Scientists 34
Google Scholar H5-index 34
Guide2Research Overall Ranking: 180
Category Rankings
Machine Learning & Artificial Intelligence 54
DBLP Page https://dblp.uni-trier.de/db/conf/uai

Conference Call for Papers

The list of subject areas appears to authors and reviewers in the CMT conference management system. Below you find a list 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
Recommender Systems
Reinforcement Learning
Relational Learning
Representation Learning
Semi-Supervised Learning
Structure Learning
Structured Prediction
Unsupervised Learning
Models
Bandits
(Dynamic) Bayesian Networks
Generative Models
Graphical Models – Directed
Graphical Models – Undirected
Graphical Models – Mixed
Markov Decision Processes
Models for Relational Data
Neural Networks
Probabilistic Circuits
Regression Models
Spatial and Spatio-Temporal Models
Temporal and Sequential Models
Topic Models and Latent Variable Models
Principles
Explainability
Causality
Computational and Statistical Trade-Offs
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

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