1.5k citations · 3.4k across the 22 of their papers we have counts for
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In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD
Riccardo Balin, Filippo Simini, Cooper Simpson +7
Recent years have seen many successful applications of machine learning (ML) to facilitate fluid dynamic computations. As simulations grow, generating new training datasets for tra…
Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks
Ryien Hosseini, Filippo Simini, Austin Clyde +1
The process of screening molecules for desirable properties is a key step in several applications, ranging from drug discovery to material design. During the process of drug discov…
Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications
Ryien Hosseini, Filippo Simini, Venkatram Vishwanath
As Graph Neural Networks (GNNs) increase in popularity for scientific machine learning, their training and inference efficiency is becoming increasingly critical. Additionally, the…
Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information
Filippo Simini, Gianni Barlacchi, Massimiliano Luca +1
The movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment.…