Bayesian modeling

Uncertainty-Aware Learning: From Bayesian Neural Networks to Agentic Decision Making

Theodore Papamarkou, Founder, PolyShape; Visiting Professor, School of Applied Mathematical and Physical Sciences (SEMFE), National Technical University of Athens (NTUA)

Feb 1, 12:00 - 13:00

B4/5 L0 A0215

uncertainty quantification neural network Bayesian modeling AI

This talk points out that uncertainty quantification is important for reliable AI, and that modern machine learning should be viewed through the lens of probabilistic decision making.

Applied AI for sustainable development

Prof.Evgeny Burnaev, Applied AI Center, Skolkovo Institute of Science and Technology

Oct 24, 12:00 - 13:00

B9 L2 R2322 H1

Skoltech machine learning Bayesian modeling artificial intelligence

Skoltech Applied AI center’s mission is to create AI models and frameworks for solving the problems of sustainable development of industry and economy. In my presentation, I will overview the current center's activities, applied and fundamental problem statements, and corresponding recent results.