Publications associées à The PAU Survey and Euclid: Improving broadband photometric redshifts with multi-task learning star

Publications associées (15)

Euclid: The Early Release Observations Lens Search Experiment

Frédéric Courbin, Georges Meylan, Georgios Vernardos, Lucie Anemone Scharré, Bastien Clément

We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the 0.7 deg2 Euclid Early Release Observations data towards the Perseus cluster using both the high-re ...

2025

How to minimize the annotation effort in aerial wildlife surveys

Devis Tuia, Emanuele Dalsasso, Giacomo Günter May

Aircraft-based monitoring of wildlife is a popular way among conservation practitioners to obtain animal population counts over large areas. Nowadays, these aerial censuses are becoming increasingly scalable due to the advent of drone technology, which is ...

2025

The Pristine survey: XXV. The very metal-poor Galaxy: Chemodynamics through the follow-up of the Pristine- Gaia synthetic catalogue

Nicolas Lawrence Etienne Longeard

Context. The Pristine-Gaia synthetic catalogue of reliable photometric metallicities makes use of spectrophotometric information from Gaia DR3 XP spectra to calculate metallicity-sensitive CaHK magnitudes, which in turn provides photometric metallicities f ...

2025

Generative models for synthetic data generation: application to pharmacokinetic/pharmacodynamic data

Yulun Jiang

The generation of synthetic patient data that reflect the statistical properties of real data plays a fundamental role in today’s world because of its potential to (i) be enable proprietary data access for statistical and research purposes and (ii) increas ...

2024

Probing the effects of broken symmetries in machine learning

Michele Ceriotti, Sergey Pozdnyakov, Marcel Florin Langer

Symmetry is one of the most central concepts in physics, and it is no surprise that it has also been widely adopted as an inductive bias for machine-learning models applied to the physical sciences. This is especially true for models targeting the properti ...

2024

Semantic Segmentation of Coffee Plantations from Sentinel-2 Time Series

Devis Tuia, Jan Pisl, Gaston Jean Lenczner

Coffee production serves as an important source of income for millions of farmers across many tropical countries. Given the scale of the production, accurate and up-to-date maps of coffee plantations are needed to detect, monitor, and mitigate potential ne ...

Institute of Electrical and Electronics Engineers Inc.2024

Robust Training and Verification of Deep Neural Networks

Fabian Ricardo Latorre Gomez

According to the proposed Artificial Intelligence Act by the European Comission (expected to pass at the end of 2023), the class of High-Risk AI Systems (Title III) comprises several important applications of Deep Learning like autonomous driving vehicles ...

EPFL2023

Constraints on the Hubble constant from supernova Refsdal's reappearance

Vivien François Bonvin, Martin Raoul Robert Millon

The gravitationally lensed supernova Refsdal appeared in multiple images produced through gravitational lensing by a massive foreground galaxy cluster. After the supernova appeared in 2014, lens models of the galaxy cluster predicted that an additional ima ...

American Association for the Advancement of Science2023

Automated image-based generation of finite element models for masonry buildings

Katrin Beyer, Radhakrishna Achanta, Bryan German Pantoja Rosero

To predict the response of masonry buildings to various types of loads, engineers use finite element models, specifically solid-element and macro-element models. For predicting masonry responses to seismic events in particular, equivalent frame models-a su ...

SPRINGER2023

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

Sokratis Anagnostopoulos

Wind farm modelling is an area of rapidly increasing interest with numerous analytical and computational-based approaches developed to extend the margins of wind farm efficiency and maximise power production. In this work, we present the novel ML framework ...

Pergamon-Elsevier Science Ltd2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

STATNet: Spatial-temporal attention in the traffic prediction

Alexandre Massoud Alahi

Recent traffic flow prediction methods are lacking abilities to determine predictive features. Thus, they will propagate the error in the next timestamps. In this paper, first, we assess the role of spatial and temporal features on the traffic speed predic ...

2022

PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers

Mathieu Salzmann, Helge Jochen Rhodin

Local processing is an essential feature of CNNs and other neural network architectures - it is one of the reasons why they work so well on images where relevant information is, to a large extent, local. However, perspective effects stemming from the proje ...

2021

Context-Aware Image Super-Resolution Using Deep Neural Networks

Mohammad Saeed Rad

Image super-resolution is a classic ill-posed computer vision and image processing problem, addressing the question of how to reconstruct a high-resolution image from its low-resolution counterpart. Current state-of-the-art methods have improved the perfor ...

EPFL2021

Architecture Exploration and Optimization of Heterogeneous Many-Core Compute and Memory Architectures with Architectural Extensions

Yasir Mahmood Qureshi

The expeditious proliferation of Internet connectivity and the growing adoption of digital products have transformed various spheres of our everyday lives. This increased digitization of society has led to the emergence of new applications, which are deplo ...

EPFL2021