Uncertainty in Artificial Intelligence Courses

The Power of Cooperation in Networks of Learning Agents - Keynote Talk

Explore the power of cooperation in agent networks for enhanced learning, focusing on performance bounds and online learning scenarios.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Causality in Artificial Intelligence - Oral Session 3

Explore cutting-edge research in causal inference, including bounding effects, model reduction, interventions in games, and causally abstracted bandits.

• YouTube
• 1 hour 35 minutes
• On-Demand
• Free Video

Geometric Probabilistic Models - Tutorial 4

Explore geometric probabilistic models for data-efficient, uncertainty-aware decision-making in applications like drug design and robotics. Learn theory and implementation of Gaussian processes and related techniques.

• YouTube
• 2 hours 32 minutes
• On-Demand
• Free Video

Introduction to Performative Prediction - Tutorial 1

Explore performative prediction in machine learning, examining its impact on data distribution, equilibrium challenges, and connections to statistics, game theory, and causality. Gain insights into steering and power dynamics in digital markets.

• YouTube
• 3 hours 10 minutes
• On-Demand
• Free Video

Probabilistic Modeling and Decision Making - Oral Session 6

Explore advanced topics in probabilistic modeling and decision-making, including facility location, answer set programs, utility theory, and probabilistic circuits.

• YouTube
• 1 hour 32 minutes
• On-Demand
• Free Video

Learning Algorithms in Uncertainty and AI - Session 5

Explore cutting-edge research on cost-sensitive failure recognition, interpretable decision trees, and Bayesian active learning in AI. Gain insights into advanced learning algorithms and their applications.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Sequential Learning in Artificial Intelligence - Oral Session 4

Explore cutting-edge research in sequential learning, covering robust reinforcement learning, online learning in MDPs, fairness in predict-then-optimize settings, and constrained POMDPs.

• YouTube
• 1 hour 33 minutes
• On-Demand
• Free Video

Deep Learning Advances in Uncertainty and Generative Modeling - Session 1

Explore cutting-edge deep learning research, including Bayesian methods, generative modeling, visual concept programming, conformal regression, and heteroskedastic regression analysis.

• YouTube
• 2 hours 3 minutes
• On-Demand
• Free Video

All Causal DAGs Are Wrong but Some Are Useful

Explore the concept of causal DAGs, their usefulness, and challenges in causal discovery. Gain insights into evaluating causal models without ground truth and understanding causality's meaning across various tasks.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Probabilistic Circuits That Know What They Don't Know - UAI Oral Session 6

Explore probabilistic circuits' robustness to out-of-distribution data and learn about tractable dropout inference for improved uncertainty quantification in a single forward pass.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Probabilistic Flow Circuits: Towards Deep Models for Tractable Inference - Oral Session 6

Explore a novel approach combining probabilistic circuits with normalizing flows for enhanced expressivity while maintaining tractable inference in deep probabilistic models.

• YouTube
• 27 minutes
• On-Demand
• Free Video

On Inference and Learning With Probabilistic Generating Circuits

Explore efficient inference algorithms for Probabilistic Generating Circuits, addressing computational challenges and discussing implications for learning from data in probabilistic modeling.

• YouTube
• 22 minutes
• On-Demand
• Free Video

Local Message Passing on Frustrated Systems - UAI Oral Session 6

Explore an alternative message passing algorithm for cyclic graphs, challenging SPA's extrinsic principle and optimizing factor node updates for improved performance on complex networks.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Revisiting Bayesian Network Learning with Small Vertex Cover

Explore Bayesian network structure learning with bounded vertex cover, analyzing complexity bounds and hardness results for optimization and counting problems.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Causal Representation Learning and Optimal Intervention Design

Explore causal representation learning and optimal intervention design with Caroline Uhler's insightful keynote talk at UAI 2023.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video