Search Results for author: Filippo Simini

Found 7 papers, 7 papers with code

Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks

1 code implementation4 Nov 2022 Ryien Hosseini, Filippo Simini, Austin Clyde, Arvind Ramanathan

The process of screening molecules for desirable properties is a key step in several applications, ranging from drug discovery to material design.

Drug Discovery

Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications

1 code implementation20 Jul 2022 Ryien Hosseini, Filippo Simini, Venkatram Vishwanath

At a high level, we conclude that on NVIDIA systems: (1) confounding bottlenecks such as memory inefficiency often dominate runtime costs moreso than data sparsity alone, (2) native Pytorch operations are often as or more competitive than their Pytorch Geometric equivalents, especially at low to moderate levels of input data sparsity, and (3) many operations central to state-of-the-art GNN architectures have little to no optimization for sparsity.

Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information

1 code implementation1 Dec 2020 Filippo Simini, Gianni Barlacchi, Massimiliano Luca, Luca Pappalardo

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.

The agglomeration and dispersion dichotomy of human settlements on Earth

1 code implementation11 Jun 2020 Emanuele Strano, Filippo Simini, Marco De Nadai, Thomas Esch, Mattia Marconcini

To explain the observed spatial patterns, we also propose a model that combines two agglomeration forces and simulates human settlements' historical growth.

Physics and Society

Social media usage reveals how regions recover after natural disaster

1 code implementation20 Aug 2019 Robert Eyre, Flavia De Luca, Filippo Simini

The challenge of nowcasting and forecasting the effect of natural disasters (e. g. earthquakes, floods, hurricanes) on assets, people and society is of primary importance for assessing the ability of such systems to recover from extreme events.

Physics and Society Computers and Society Applications

Scikit-mobility: a Python library for the analysis, generation and risk assessment of mobility data

6 code implementations8 Jul 2019 Luca Pappalardo, Gianni Barlacchi, Filippo Simini, Roberto Pellungrini

The last decade has witnessed the emergence of massive mobility data sets, such as tracks generated by GPS devices, call detail records, and geo-tagged posts from social media platforms.

Physics and Society

Data-driven generation of spatio-temporal routines in human mobility

1 code implementation16 Jul 2016 Luca Pappalardo, Filippo Simini

DITRAS operates in two steps: the generation of a mobility diary and the translation of the mobility diary into a mobility trajectory.

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