Publications associées à Learning to Simulate Realistic LiDARs

Publications associées (33)

Improvements to the dynamic wake meandering model by incorporating the turbulent Schmidt number

Fernando Porté Agel, Peter Andreas Brugger, Corey Dean Markfort

Predictions of the dynamic wake meandering model (DWMM) were compared to flow measurements of a scanning Doppler lidar mounted on the nacelle of a utility-scale wind turbine. We observed that the wake meandering strength of the DWMM agrees better with the ...

2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Stellar Metallicities and Gradients in the Isolated, Quenched Low-mass Galaxy Tucana

Nicolas Lawrence Etienne Longeard

We measure the metallicities of 374 red giant branch (RGB) stars in the isolated, quenched dwarf galaxy Tucana using Hubble Space Telescope (HST) narrow-band (F395N) Calcium H & K (CaHK) imaging. Our sample is a factor of similar to 7 similar to 7 larger t ...

Iop Publishing Ltd2024

Understanding snow saltation parameterizations: lessons from theory, experiments and numerical simulations

Michael Lehning, Armin Sigmund, Daniela Brito Melo

Drifting and blowing snow are important features in polar and high mountain regions. They control the surface mass balance in windy conditions and influence sublimation of snow and ice surfaces. Despite their importance, model representations in weather an ...

2024

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

Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

Bryan German Pantoja Rosero

Current post-earthquake damage assessment methodologies are not only time-consuming but also subjective in nature and difficult to document. Recent advancements in artificial intelligence and technological devices make it possible to accomplish this task a ...

EPFL2023

Timelapse: Rhone mouth in Geneva Lake - 2022

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2022. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2023

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute from January to August 2023. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2021

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2021. ...

EPFL Infoscience2023

Timelapse: Geneva Lake, in front of Chexbres - 2019

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2017

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2017. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2019

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019. ...

EPFL Infoscience2023

Search for Higgs boson pairs decaying to WWWW, WW*ττ, and ττττ in proton-proton collisions at √s=13 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Lei Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Jessica Prisciandaro, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Guido Andreassi, Arvind Shah, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Gabriele Grosso

The results of a search for Higgs boson pair (HH) production in the (WWWW*)-W-, WWtau tau, and tau tau tau tau decay modes are presented. The search uses 138 fb(-1) of proton-proton collision data recorded by the CMS experiment at the LHC at a center-of- ...

Springer Nature2023

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

2023

BamX: Rethinking Deployability in Architecture through Weaving

Mark Pauly, Stefana Parascho, Tian Chen, Yingying Ren, Seiichi Eduardo Suzuki Erazo

Deployable gridshells are a class of planar-to-spatial structures that achievea 3D curved geometry by inducing bending on a flat grid of elastic beams. However, theslender nature of these beams often conflicts with the structure’s load-bearing capacity.To ...

De Gruyter2023

An experimental and analytical study of wind turbine wakes under pressure gradient

Fernando Porté Agel, Arslan Salim Dar

This work is dedicated to the systematic investigation of wind turbine wakes under the effect of pressure gradients. Wind tunnel experiments are carried out with a wind turbine positioned on straight ramps of increasing angle such that it experiences an ap ...

2023

Text Representation Learning for Low Cost Natural Language Understanding

Jan Frederik Jonas Florian Mai

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

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

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Alexandre Massoud Alahi, Dolaana Khovalyg, Mohamad Rida, Mohamed Ossama Ahmed Abdelfattah

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

2023

"A physics-based model for wind turbine wake expansion in the atmospheric boundary layer"

Fernando Porté Agel, Dara Vahidi

Vahidi, Dara, and Fernando Porté-Agel. "A physics-based model for wind turbine wake expansion in the atmospheric boundary layer." Journal of Fluid Mechanics 943 (2022). ...

Zenodo2022