Publications related to Toward a Collective Agenda on AI for Earth Science Data Analysis

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Marco Fedele, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

Simulated Learners in Educational Technology: A Systematic Literature Review and a Turing-like Test

Tanja Christina Käser Jacober

Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be use ...

SPRINGER2023

In situ monitoring of femtosecond laser-induced modifications in dielectrics

Olivier Bernard

Over the last decades, the progress made in the generation of laser pulses shorter than a picosecond (10^-12 s) has allowed us to reach extreme optical power intensities exceeding 10^15 W cm^-2. This tremendous power has triggered an abundance of original ...

EPFL2023

Towards Efficient Gas Leak Detection in Built Environments: Data-Driven Plume Modeling for Gas Sensing Robots

Alcherio Martinoli, Faezeh Rahbar, Chiara Ercolani, Wanting Jin

The deployment of robots for Gas Source Lo- calization (GSL) tasks in hazardous scenarios significantly reduces the risk to humans and animals. Gas sensing using mobile robots focuses primarily on simplified scenarios, due to the complexity of gas dispersi ...

2023

Divide-and-conquer one-step simulator for the generation of synthetic households

Michel Bierlaire, Marija Kukic

This paper presents a novel simulation approach for generating synthetic households, addressing several literature gaps from the methodological viewpoint. The generation of hierarchical datasets such as complete households is challenging since it must guar ...

2023

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Stephen William Wasilewski

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

EPFL2023

Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs

Mahsa Shoaran, Mohammad Ali Shaeri, Arshia Afzal

Neuroscience and neurotechnology are currently being revolutionized by artificial intelligence (AI) and machine learning. AI is widely used to study and interpret neural signals (analytical applications), assist people with disabilities (prosthetic applica ...

IEEE2022

Efficient Simulation for Visual Comfort Evaluations

Marilyne Andersen, Jan Wienold, Stephen William Wasilewski

This paper provides a validation of a novel sampling, storage, and evaluation method named raytraverse that can quickly and accurately compute glare and visual comfort metrics including vertical illuminance, Daylight Glare Probability (DGP), and Unified Gl ...

2022

LeXPLORE: A floating laboratory on Lake Geneva offering unique lake research opportunities

Natacha Tofield-Pasche, Alfred Johny Wüest, Sébastien Lavanchy, Damien Bouffard

Environmental sciences depend heavily on observational data. Successful studies of ecological processes in lakes require in-situ data that cover the relevant temporal scales from milliseconds to entire seasons. Temporal and spatial coverage requirements re ...

2021

Simulation and experimental study of proton bunch self-modulation in plasma with linear density gradients

Patrick Blanchard, Ambrogio Fasoli, Ivo Furno, Yanis Andrebe, Alban Sublet, Sun Hee Kim, Falk Hans Braunmüller, Riccardo Agnello, Christine Stollberg

We present numerical simulations and experimental results of the self-modulation of a long proton bunch in a plasma with linear density gradients along the beam path. Simulation results agree with the experimental results reported [F. Braunmller, T. Nechae ...

2021

Low Noise Clock Generation: Modeling, Analysis and Implementation

Duygu Kostak

The aim of this thesis is to implement, analyze and improve the selected low noise clock generation and distribution techniques for ADC implementations. The thesis is divided into two parts. The first part focuses on the sampling phase generation and distr ...

EPFL2021

Towards Efficient and Accurate Numerical Simulations of Galaxies using Task-based Parallelism and Application to Dwarf Galaxies

Loïc Hausammann

Numerical simulations are of a tremendous help to understand the growth of non-linear cosmological structures and how they lead to the formation of galaxies. In recent years, with the goal of improving their prediction power, new hydrodynamical techniques ...

EPFL2021

Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences

Devis Tuia

Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered a ...

Wiley2021

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

Claudio Bruschini, Edoardo Charbon, Ivan Michel Antolovic, Mario Stipcevic

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

SPIE2021

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

François Maréchal, Ivan Daniel Kantor, Julia Granacher

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

2021

Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics

Alfio Quarteroni, Francesco Regazzoni

High fidelity (HF) mathematical models describing the generation of active force in the cardiac muscle tissue typically feature a large number of state variables to capture the intrinsically complex underlying subcellular mechanisms. With the aim of drasti ...

2020

Computational characteristics and hardware implications of brain tissue simulations

Francesco Cremonesi

Understanding the link between the brain's anatomy and its function through computer simulations of neural tissue models is a widely used approach in computational neuroscience. This technique enables rapid prototyping and testing of hypotheses, allowing r ...

EPFL2019

Nonperturbative test of consistency relations and their violation

Angelo Esposito

In this paper, we verify the large scale structure consistency relations using N-body simulations, including modes in the highly nonlinear regime. These relations (pointed out by Kehagias & Riotto and Peloso & Pietroni) follow from the symmetry of the dyna ...

American Physical Society2019

Ethics in Research

Science is in revolution. The formidable scientific and technological developments of the last century have dramatically transformed the way in which we conduct scientific research. The knowledge and applications that science produces has profound conseque ...

2019

Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

Yan Yan, Gaowen Liu, Wei Wang

In this work, we propose a novel Cycle In Cycle Generative Adversarial Network (C2GAN) for the task of keypoint-guided image generation. The proposed C2GAN is a cross-modal framework exploring a joint exploitation of the keypoint and the image data in an i ...

ASSOC COMPUTING MACHINERY2019