Explore uncertainty quantification in quantum chemical methods through this 42-minute conference talk presented by Markus Reiher from ETH Zurich at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Delve into topics such as automation, kinetic modeling, transferability, discretization errors, benchmark results, and continuous benchmarking. Examine knowledge-based error estimation, Gaussian processes, reaction network exploration, and multiconfiguration DMRG. Discover entanglement measures, selection algorithms, and user interfaces for quantum chemical calculations. Learn about reference data, D3 correction, training data, and automated workflows in the context of quantum chemistry. Gain insights into the fundamental problems and challenges in quantifying uncertainties in quantum chemical methods, and understand the importance of error compensation and data-driven machine learning approaches in this field.