3 papers
cs.AI2026
Position: agentic AI orchestration should be Bayes-consistent
Theodore Papamarkou, Pierre Alquier, Matthias Bauer +27
LLMs excel at predictive tasks and complex reasoning tasks, but many high-value deployments rely on decisions under uncertainty, for example, which tool to call, which expert to co…
cs.LG2026
Enhancing the Reliability of Medical AI through Expert-guided Uncertainty Modeling
Aleksei Khalin, Ekaterina Zaychenkova, Aleksandr Yugay +4
Artificial intelligence (AI) systems accelerate medical workflows and improve diagnostic accuracy in healthcare, serving as second-opinion systems. However, the unpredictability of…
cs.LG2026
Strong Linear Baselines Strike Back: Closed-Form Linear Models as Gaussian Process Conditional Density Estimators for TSAD
Aleksandr Yugay, Hang Cui, Changhua Pei +1
Research in time series anomaly detection (TSAD) has largely focused on developing increasingly sophisticated, hard-to-train, and expensive-to-infer neural architectures. We revisi…