Due to the vast amount of data collected and the very high level of complexity in VLSI design and manufacturing, the implementation using machine learning can be used in physical design has increased significantly. ML can be used to increase the abstraction level that is obtained from complex simulations based on physics models and provide results that represent a significant level of quality. Computer science techniques such as pattern matching and machine learning can reduce the design time of VLSI circuits by working with large datasets. © 2023 Elsevier B.V., All rights reserved.