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Related publications (29)

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Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Frédéric Kaplan, Isabella Di Lenardo, Rémi Guillaume Petitpierre, Beatrice Vaienti

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

2023

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Li Zhang, Jiancheng Yang

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Springer International Publishing Ag2023

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Saeed Saadatnejad

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

EPFL2023

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Henry Markram, Sean Lewis Hill, Alejandra Garcia Rojas Martinez, Huanxiang Lu, Mohameth François Sy, Anna-Kristin Kaufmann, Samuel Claude Kerrien, Alexander Désiré Ulbrich, Henry Genet, Pierre-Alexandre Fonta, Silvia Rosario Jimenez Tejeda, Michaël Fernand Paul Dupont, Bogdan Roman, Ian Lavriushev, Didac Montero Mendez, Wojciech Adam Wajerowicz, Kenneth William Pirman, Julien Antonin Machon, Jonathan Raël Lurie, Dhanesh Neela Mana, Natalia Stafeeva, Carolina Johanna Elisabeth Lindqvist

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

2023

Friction and fracture: richness and complexity in dynamic rupture

Thibault Didier Roch

Understanding how things break and slide is of paramount importance to describe the dynamics of a broad range of physical systems. This includes day-to-day problems such as the breaking of a glass of wine or the sliding of skis on snow, but also engineerin ...

EPFL2023

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Zilu Tian

Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

EPFL2023

SwissCovid in the Perspective of Its Goals

Serge Vaudenay, Martin Vuagnoux

SwissCovid is the Swiss digital contact tracing app, which was deployed to help fighting against the COVID-19 pandemic. After a year of activity, it is high time to evaluate how effective it has been in its mission. At the highest peak, about 22% of the Sw ...

2022

ShapePipe: A modular weak-lensing processing and analysis pipeline

Austin Chandler Peel

We present the first public release of ShapePipe, an open-source and modular weak-lensing measurement, analysis, and validation pipeline written in Python. We describe the design of the software and justify the choices made. We provide a brief description ...

2022

Structural characterisation of nanoalloys for (photo)catalytic applications with the Sapphire library

Kevin Rossi

A non-trivial interplay rules the relationship between the structure and the chemophysical properties of a nanoparticle. In this context, characterization experiments, molecular dynamics simulations and electronic structure calculations may allow the varia ...

ROYAL SOC CHEMISTRY2022