Uncertainty quantification (UQ) is increasingly critical for modelling complex systems in which input parameters or environmental conditions vary unpredictably. Polynomial chaos methods offer a ...

Abstract: The increasing power of computing platforms and the recent advances in data science techniques have fostered the development of data-driven computational models of engineering systems with ...

In Chapter 1, verification is defined as the process of determining how accurately a computer program (“code”) correctly solves the equations of a mathematical model. This includes code verification ...

AI is becoming more capable, but research shows it often falters in how it reasons—especially in high-stakes fields like healthcare, law, and drug discovery. Studies reveal large language models can ...

MIT researchers have developed a reinforcement learning method, RLCR, that trains AI models to provide calibrated confidence estimates alongside answers, reducing overconfidence by up to 90% without ...