Power-law of Aggregate-size Spectra in Natural Systems. - Matteo Convertino; Filippo Simini; Filippo Catani; Igor Linkov; Gregory A. Kiker (EAI Endorsed Trans. Complex Syst., 2013)

Evacuation time estimate for a total pedestrian evacuation using queuing network model and volunteered geographic information. - Bharat Kunwar; Filippo Simini; Anders Johansson (CoRR, 2015)

Human Mobility Modelling: Exploration and Preferential Return Meet the Gravity Model. - Luca Pappalardo; Salvatore Rinzivillo; Filippo Simini (ANT/SEIT, 2016)

Modelling individual routines and spatio-temporal trajectories in human mobility. - Luca Pappalardo; Filippo Simini (CoRR, 2016)

Nanoscale artificial intelligence: creating artificial neural networks using autocatalytic reactions. - Filippo Simini (CoRR, 2016)

Sensor-Based Smart Hot-Desking for Improvement of Office Well-Being. - Keren Berelson; Filippo Simini; Theo Tryfonas; Peter Cooper (DTUC, 2018)

Prediction of next career moves from scientific profiles. - Charlotte James; Luca Pappalardo; Alina Sîrbu; Filippo Simini (CoRR, 2018)

Data-driven generation of spatio-temporal routines in human mobility. - Luca Pappalardo; Filippo Simini (Data Min. Knowl. Discov., 2018)

Human Mobility from theory to practice: Data, Models and Applications. - Luca Pappalardo; Gianni Barlacchi; Roberto Pellungrini; Filippo Simini (WWW (Companion Volume), 2019)

Social media usage reveals how regions recover after natural disaster. - Robert Eyre; Flavia De Luca; Filippo Simini (CoRR, 2019)

Testing Heaps' law for cities using administrative and gridded population data sets. - Filippo Simini; Charlotte James (EPJ Data Sci., 2019)

Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information. - Filippo Simini; Gianni Barlacchi; Massimiliano Luca; Luca Pappalardo (CoRR, 2020)

Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems. - Shilpika; Bethany Lusch; Murali Emani; Filippo Simini; Venkatram Vishwanath; Michael E. Papka; Kwan-Liu Ma (CCGRID, 2022)

Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications. - Ryien Hosseini; Filippo Simini; Venkatram Vishwanath (CoRR, 2022)

Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks. - Ryien Hosseini; Filippo Simini; Austin Clyde; Arvind Ramanathan (CoRR, 2022)

scikit-mobility: A Python Library for the Analysis, Generation, and Risk Assessment of Mobility Data. - Luca Pappalardo; Filippo Simini; Gianni Barlacchi; Roberto Pellungrini (J. Stat. Softw., 2022)

Modeling Adversarial Behavior Against Mobility Data Privacy. - Roberto Pellungrini; Luca Pappalardo; Filippo Simini; Anna Monreale (IEEE Trans. Intell. Transp. Syst., 2022)

Exploring the Use of Dataflow Architectures for Graph Neural Network Workloads. - Ryien Hosseini; Filippo Simini; Venkatram Vishwanath; Ramakrishnan Sivakumar; Sanjif Shanmugavelu; Zhengyu Chen; Lev Zlotnik; Mingran Wang; Philip Colangelo; Andrew Deng; Philip Lassen; Shukur Pathan (ISC Workshops, 2023)

In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD. - Riccardo Balin; Filippo Simini; Cooper Simpson; Andrew Shao; Alessandro Rigazzi; Matthew Ellis; Stephen Becker; Alireza Doostan; John A. Evans; Kenneth E. Jansen (CoRR, 2023)

A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. - Shilpika; Bethany Lusch; Murali Emani; Filippo Simini; Venkatram Vishwanath; Michael E. Papka; Kwan-Liu Ma (CCGrid, 2024)

A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation. - Ryien Hosseini; Filippo Simini; Venkatram Vishwanath; Henry Hoffmann (AAAI, 2025)

Quality Measures for Dynamic Graph Generative Models. - Ryien Hosseini; Filippo Simini; Venkatram Vishwanath; Rebecca Willett; Henry Hoffmann (ICLR, 2025)