Abstract
Deep learning models have become crucial in various domains and applications that benefit from scientific computing. Furthermore, the execution time of these models is critical to meeting the ever-growing demands in many areas. One example is the problem of predicting molecular properties, where the model's execution time is crucial when the system needs to perform multiple real-time pred…