Publications associées à reference radiance model and result data for an office building near LAX

Publications associées (29)

PlaceNet: A multi-scale semantic-aware model for visual loop closure detection

Loop closure detection helps simultaneous localization and mapping systems reduce map and state uncertainty via recognizing previously visited places along the path of a mobile robot. However, visual loop closure detection is susceptible to scenes with dyn ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Digitised Newspapers – A New Eldorado for Historians? Reflections on Tools, Methods and Epistemology

Maud Ehrmann

The application of digital technologies to historical newspapers has changed the research landscape historians were used to. An Eldorado? Despite undeniable advantages, the new digital affordance of historical newspapers also transforms research practices ...

De Gruyter2022

Augmenting the performance of impoverished sensor networks using machine learning and time reversal: Application to lightning nowcasting and location

Amirhossein Mostajabi

Lightning is formed in the atmosphere through the combination of intricate dynamic and microphysical processes. Mainly due to this complexity, attempts to solve the important problem of lightning prediction have generally failed to yield accurate results. ...

EPFL2021

Data mining in the context of urban metabolism: A case study of Geneva and Lausanne, Switzerland

Claudia Rebeca Binder Signer, Aristide Henri Roger Athanassiadis

The highest share of the global population lives in cities. The current configuration of the latter requires considerable amounts of resource flows causing the degradation of local and global ecosystems. To face the complexity of these challenges, scientis ...

IOP PUBLISHING LTD2021

Sparse multi-view hand-object reconstruction for unseen environments

Andrea Cavallaro

Recent works in hand-object reconstruction mainly focus on the single-view and dense multi-view settings. On the one hand, single-view methods can leverage learned shape priors to generalise to unseen objects but are prone to inaccuracies due to occlusions ...

IEEE2024

Leveraging large language models for predictive chemistry

Berend Smit, Philippe Schwaller, Kevin Maik Jablonka, Andres Adolfo Ortega Guerrero

Machine learning has transformed many fields and has recently found applications in chemistry and materials science. The small datasets commonly found in chemistry sparked the development of sophisticated machine learning approaches that incorporate chemic ...

Nature Portfolio2024

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Pascal Fua, Mathieu Salzmann, Andrey Davydov

When enough annotated training data is available, supervised deep-learning. algorithms excel at estimating human body pose and shape using a single camera. The effects of too little such data being available can be mitigated by using other information sour ...

Journal of Machine Learning Research Inc.2024

Electronic Excited States from Physically Constrained Machine Learning

Michele Ceriotti, Jigyasa Nigam, Divya Suman

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

2024

Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques

Farhad Rachidi-Haeri, Marcos Rubinstein, Amirhossein Mostajabi

Article Open Access Published: 08 November 2019 Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques Amirhossein Mostajabi, Declan L. Finney, Marcos Rubinstein & Farhad Rachidi npj Climate and ...

2019

Efficient Bundled Spatial Range Queries

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Eleni Tzirita Zacharatou, Darius Sidlauskas

Efficiently querying multiple spatial data sets is a growing challenge for scientists. Astronomers query data sets that contain different types of stars (e.g., dwarfs, giants, stragglers) while neuroscientists query different data sets that model different ...

ASSOC COMPUTING MACHINERY2019

Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Zenodo2024

Design of approximate and precision-scalable circuits for embedded multimedia and neural-network processing

Vincent Frédéric Camus

Density, speed and energy efficiency of integrated circuits have been increasing exponentially for the last four decades following Moore's law. However, power and reliability pose several challenges to the future of technology scaling. Approximate computin ...

EPFL2019

An Analysis of Lightning Activity in the Säntis Region through the Big Hiatus in Global Warming

Farhad Rachidi-Haeri, Marcos Rubinstein, Mohammad Azadifar, Amirhossein Mostajabi, Aleksandr Smorgonskii

The response of local lightning to local surface temperature is examined near the Säntis mountain (2502 m ASL) in the eastern Swiss Alps during the first of the two hiatuses in global warming covering the time periods 1940-1972 and 1998-2014. The mountain ...

2018

Spatial interpolation of precipitation from multiple rain gauge networks and weather radar data for operational applications in Alpine catchments

Giovanni De Cesare, Bettina Schaefli, Javier García Hernández, Alain Tommy Foehn

Increasing meteorological data availability and quality implies an adaptation of the interpolation methods for data combination. In this paper, we propose a new method to efficiently combine weather radar data with data from two heated rain gauge networks ...

2018

High performance computation of landscape genomic models including local indicators of spatial association

Stéphane Joost, Sylvie Stucki, Solange Catherine Gaillard

With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics — i.e. the combination of landscape ecology with population genomics — include processing large numbers of models and distinguishing be ...

Wiley-Blackwell2017

Gaussian Multiple Access via Compute-and-Forward

Michael Christoph Gastpar, Jingge Zhu

Lattice codes used under the compute-and-forward paradigm suggest an alternative strategy for the standard Gaussian multiple-access channel (MAC): the receiver succes- sively decodes the integer linear combinations of the messages until it can invert and r ...

Institute of Electrical and Electronics Engineers2017

Measurements of precipitation in Dumont d'Urville, Adelie Land, East Antarctica

Alexis Berne, Jacopo Grazioli

The first results of a campaign of intensive observation of precipitation in Dumont d'Urville, Antarctica, are presented. Several instruments collected data from November 2015 to February 2016 or longer, including a polarimetric radar (MXPol), a Micro Rain ...

Copernicus GmbH2017

Toward timely, predictable and cost-effective data analytics

Renata Borovica-Gajic

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

EPFL2016

Los desafíos de la modelización hidrológica y la previsión de crecidas en tiempo real en alta montaña

Anton Schleiss, Javier García Hernández, Alain Tommy Foehn

Flood forecasting systems are today recognized as a key element in natural hazard mitigation. The objective is to exploit the available observed and forecasted meteorological information to foresee river discharges up to several days in advance, using a hy ...

2016

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Ntorina Thanou, Nicola Parolini, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Andrea Kraus, David Kraus

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023