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Publications associées (29)

OASIS: An integrated optimisation framework for activity scheduling

Activity-based models offer the potential for a far deeper understanding of daily mobility behaviour than trip-based models. Based on the fundamental assumption that travel demand is derived from the need to do activities, they are flexible tools that aim ...

EPFL2024

Artificial intelligence of things for synergizing smarter eco-city brain, metabolism, and platform: Pioneering data-driven environmental governance

Jeffrey Huang, Simon Elias Bibri

Emerging smarter eco-cities, inherently intertwined with environmental governance, function as experimental sites for testing novel technological solutions and implementing environmental reforms aimed at addressing complex challenges. However, despite sign ...

Elsevier2024

Neutrino Signal from a Population of Seyfert Galaxies

Andrii Neronov

IceCube Collaboration has previously reported evidence for a neutrino signal from a Seyfert galaxy NGC 1068. This may suggest that all Seyfert galaxies emit neutrinos. To test this hypothesis, we identify the best candidate neutrino sources among nearby Se ...

Amer Physical Soc2024

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Dimitrios Kyritsis, Jinzhi Lu

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...

Pergamon-Elsevier Science Ltd2024

To Infinity, and Beyond (Coverage)

Ahmad Hazimeh

The pursuit of software security and reliability hinges on the identification and elimination of software vulnerabilities, a challenge compounded by the vast and evolving complexity of modern systems. Fuzzing has emerged as an indispensable technique for b ...

EPFL2024

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Dolaana Khovalyg, Sarah Wael Ahmed Crosby

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountabili ...

2023

Discussion of ‘Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment’, part 2

Mats Julius Stensrud, Aaron Leor Sarvet

Imai et al.(IJGHS) have conducted a timely experiment on evaluating a decision support algorithm. However, we are concerned by their choice of estimands which, even if they appear plausible at first, rely on notions and assumptions for which we cannot ever ...

2023

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

Predicting party switching through machine learning and open data

Silvestro Micera

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

CELL PRESS2023

A Research-Practice Partnership to Introduce Computer Science in Secondary School: Lessons from a Pilot Program

Francesco Mondada, Barbara Bruno, Jessica Elke Dehler Zufferey, Laila Abdelsalam El-Hamamsy, Helena Kovacs, Jean-Philippe Pellet

Context: Introducing Computer Science (CS) into formal education can be challenging, notably when considering the numerous stakeholders involved which include the students, teachers, schools, and policy makers. We believe these perspectives should be con ...

2023

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Marcello Ienca

Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinica ...

ELSEVIER SCIENCE INC2023

Generating Controlled Physics-Informed Time-to-failure Trajectories for Prognostics in Unseen Operational Conditions

Olga Fink

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...

Research Publishing2023

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Olga Fink

2023

TGF beta-mediated MMP13 secretion drives myoepithelial cell dependent breast cancer progression

Cathrin Brisken, Andrea Agnoletto

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer. Virtually all women with DCIS are treated, despite evidence suggesting up to half would remain with stable, non-threatening, disease. Overtreatment thus presents a press ...

Nature Research2023

Search for dark photon decays to μ+μ- at NA62

Alina Kleimenova, Radoslav Marchevski

The NA62 experiment at CERN, designed to study the ultra-rare decay K+ -> pi(+) nu(nu) over bar, has also collected data in beam-dump mode. In this configuration, dark photons may be produced by protons dumped on an absorber and reach a decay volume beginn ...

Springer Nature2023

Language Model Decoding as Likelihood–Utility Alignment

Boi Faltings, Robert West, Maxime Jean Julien Peyrard, Debjit Paul, Valentin Hartmann, Martin Josifoski, Frano Rajic, Jiheng Wei

A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm re- main unclear. Previous works only compare decoding algorithms in narrow sc ...

Assoc Computational Linguistics-Acl2023

Atomistic modeling of C-S-H: bulk and surface

Ziga Casar

By replacing part of Portland cement with so-called supplementary cementitious materials (SCMs) it is possible to reduce the CO2 footprint of the cement industry. These SCMs are commonly limestone, calcined clay, slag and fly ash. While doing so the early ...

EPFL2023

Modeling and Optimization of Ridesplitting Operations

Caio Vitor Beojone

Ridesourcing has driven a lot of attention in recent years with the expansion of companies like Uber, Lift, and many others around the world. Companies use mobile applications connected through the internet to match drivers and their passengers real-time. ...

EPFL2023

Ricca's factors as mobile proteinaceous effectors of electrical signaling

Jian Wang, Satyam Tiwari

Leaf-feeding insects trigger high-amplitude, defense-inducing electrical signals called slow wave potentials (SWPs). These signals are thought to be triggered by the long-distance transport of low molecular mass elicitors termed Ricca's factors. We sought ...

CELL PRESS2023