Publications associées à Modeling lens potentials with continuous neural fields in galaxy-scale strong lenses

Publications associées (14)

Euclid: Early Release Observations – Dwarf galaxies in the Perseus galaxy cluster

Frédéric Courbin, Georges Meylan, Pascale Jablonka

We make use of the unprecedented depth, spatial resolution, and field of view of the Euclid Early Release Observations (EROs) of the Perseus galaxy cluster to detect and characterise the dwarf galaxy population in this massive system. Using a dedicated ann ...

2025

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Zenodo2024

Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks

Philip Neil Garner

Understanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning frameworks ...

2024

On the origin of star formation quenching in massive galaxies at z ≳ 3 in the cosmological simulations Illustris TNG

Michaela Hirschmann, Marion Nancy Amandine Farcy

Using the cosmological simulations IllustrisTNG, we perform a comprehensive analysis of quiescent, massive galaxies at z ≳ 3. The goal is to understand what suppresses their star formation so early in cosmic time, and how other similar mass galaxies remain ...

2024

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Julian Thomas Blackwell, Tanja Christina Käser Jacober, Paola Mejia Domenzain, Vinitra Swamy

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

2024

Multilingual Vision-Language Pre-training for the Remote Sensing Domain

Devis Tuia

Methods based on Contrastive Language-Image Pre-training (CLIP) are nowadays extensively used in support of vision-and-language tasks involving remote sensing data, such as cross-modal retrieval. The adaptation of CLIP to this specific domain has relied on ...

Association for Computing Machinery, Inc2024

Butterfly effects in perceptual development: A review of the 'adaptive initial degradation' hypothesis

Lukas Vogelsang

Human perceptual development evolves in a stereotyped fashion, with initially limited perceptual capabilities maturing over the months or years following the commencement of sensory experience into robust proficiencies. This review focuses on the functiona ...

Academic Press Inc Elsevier Science2024

SPAHM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations

Anne-Clémence Corminboeuf, Alberto Fabrizio, Ksenia Briling, Yannick Calvino Alonso

Recently, we introduced a class of molecular representations for kernel-based regression methods─the spectrum of approximated Hamiltonian matrices (SPAHM)─that takes advantage of lightweight one-electron Hamiltonians traditionally used as a self-consistent ...

2024

Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial

Michaël Unser, Thanh-An Michel Pham, Jonathan Yuelin Dong

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven to develop phase-retrieval algorithms. Classical approaches involve techniqu ...

2023

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Mathias Josef Payer, Chunmin Zhang, Zhiyao Feng

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Usenix Assoc2023

Time-delay estimation in unresolved lensed quasars

Georgios Vernardos

Time-delay cosmography can be used to infer the Hubble parameter H-0 by measuring the relative time delays between multiple images of gravitationally lensed quasars. A few of such systems have already been used to measure H-0: Their time delays were determ ...

OXFORD UNIV PRESS2022

TOCOSMO VIII. A key test of systematics in the hierarchical method of time-delay cosmography

Frédéric Courbin

The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of H-0. A Bayesian hierarchical framework has been propo ...

EDP SCIENCES S A2022

Finding quadruply imaged quasars with machine learning - I. Methods

Cameron Alexander Campbell Lemon

Strongly lensed quadruply imaged quasars (quads) arc extraordinary objects. They arc very rare in the sky and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distrib ...

2022

Quantization for Distributed Processing and Learning of Structured Data

Isabela Cunha Maia Nobre

In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

EPFL2022