Publications related to Methods for strong gravitational lens detection and analysis using machine learning and high performance computing

Related publications (51)

LIONHEART: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles

David Atienza Alonso, Giovanni Ansaloni, Marina Zapater Sancho, Irem Boybat Kara, Flavio Ponzina, Joshua Alexander Harrison Klein, Yuxuan Wang, Abu Sebastian

When arranged in a crossbar configuration, resistive memory devices can be used to execute Matrix-Vector Multiplications (MVMs), the most dominant operation of many Machine Learning (ML) algorithms, in constant time complexity. Nonetheless, when performing ...

Institute of Electrical and Electronics Engineers (IEEE)2025

LXXI. Simulations and nonlinearities beyond ΛCDM. 3. Constraints on f(R) models from the photometric primary probes

Frédéric Courbin, Georges Meylan

We study the constraint on f(R) gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu–Sawicki f(R) grav ...

2025

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Thomas Grégoire Stegmüller

Recent progress in computer vision has been driven by a simple yet transformative observation: the potential of 30-year-old neural networks can be unlocked by massively scaling their parameters and the amount of human-labeled training data. This breakthrou ...

EPFL2025

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

Boi Faltings, Zeki Doruk Erden

The current machine learning paradigm relies on continuous representations and fixed neural network architectures to approximate environmental structures, leading to challenges with continual learning, internal structure design, and goal-directed behavior ...

Springer Science and Business Media Deutschland GmbH2025

Euclid preparation: LXV. Determining the weak lensing mass accuracy and precision for galaxy clusters

Frédéric Courbin, Georges Meylan

The ability to measure unbiased weak-lensing (WL) masses is a key ingredient to exploit galaxy clusters as a competitive cosmological probe with the ESA Euclid survey or future missions. We investigate the level of accuracy and precision of cluster masses ...

2025

Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy

Fernando Porté Agel, Jiannong Fang, Wenlong Liao

Machine learning models (e.g., neural networks) achieve high accuracy in wind power forecasting, but they are usually regarded as black boxes that lack interpretability. To address this issue, the paper proposes a glass-box model that combines high accurac ...

2025

COSMOS-Web: Intrinsically Luminous z ≳ 10 Galaxy Candidates Test Early Stellar Mass Assembly

Michaela Hirschmann

We report the discovery of 15 exceptionally luminous 10 less than or similar to z less than or similar to 14 candidate galaxies discovered in the first 0.28 deg(2) of JWST/NIRCam imaging from the COSMOS-Web survey. These sources span rest-frame UV magnitud ...

Iop Publishing Ltd2024

Euclid: Improving the efficiency of weak lensing shear bias calibration

Frédéric Courbin, Georges Meylan, Malte Tewes

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...

Edp Sciences S A2024

Euclid and KiDS-1000: Quantifying the impact of source-lens clustering on cosmic shear analyses

Frédéric Courbin, Georges Meylan

Cosmic shear is a powerful probe of cosmological models and the transition from current Stage-III surveys such as the Kilo-Degree Survey (KiDS) to the increased area and redshift range of Stage IV surveys such as Euclid will significantly increase the prec ...

2025

Computational design of complex protein folds and soluble analogs of membrane proteins

Casper Alexander Goverde

Proteins are the molecular machines of life, driving essential biological processes such as enzymatic catalysis, cellular signaling, and immune responses. The ability to design entirely new proteins with desired structures and functions has immense implica ...

EPFL2025

XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Malte Tewes, Slobodan Ilic, Gianluca Castignani, Alessandro Pezzotta

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Univ ...

Edp Sciences S A2024

Bulk measurement of membrane permeability for random cyclic peptides in living cells to guide drug development

Nathan Moïse De Sadeleer, Christian Heinis, Alexander Lund Nielsen, Anne Sofie Luise Zarda, Rebecca Manuela Neeser

Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeability is no ...

Wiley2025

Hydrodynamical simulations of merging galaxy clusters: giant dark matter particle colliders, powered by gravity

David Richard Harvey

Terrestrial particle accelerators collide charged particles, then watch the trajectory of outgoing debris - but they cannot manipulate dark matter. Fortunately, dark matter is the main component of galaxy clusters, which are continuously pulled together by ...

Oxford Univ Press2024

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Ismail Nejjar

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

EPFL2025

Time-Delay Cosmography: Measuring the Hubble Constant and Other Cosmological Parameters with Strong Gravitational Lensing

Frédéric Courbin, Martin Raoul Robert Millon

Multiply lensed images of a same source experience a relative time delay in the arrival of photons due to the path length difference and the different gravitational potentials the photons travel through. This effect can be used to measure absolute distance ...

Springer2024

Harnessing Increased Client Participation with Cohort-Parallel Federated Learning

Anne-Marie Kermarrec, Rafael Pereira Pires, Marinus Abraham de Vos, Akash Balasaheb Dhasade, Tuan Anh Nguyen

Federated learning (FL) is a machine learning approach where nodes collaboratively train a global model. As more nodes participate in a round of FL, the effectiveness of individual model updates by nodes also diminishes. In this study, we increase the effe ...

ACM2025

Extremely Red Galaxies at z=5-9 with MIRI and NIRSpec: Dusty Galaxies or Obscured Active Galactic Nuclei?

Michaela Hirschmann

We study a new population of extremely red objects (EROs) recently discovered by the James Webb Space Telescope (JWST) based on their NIRCam colors F277W - F444W > 1.5 mag. We find 37 EROs in the Cosmic Evolution Early Release Science Survey (CEERS) field ...

Iop Publishing Ltd2024

Desi 2024 Vi: Cosmological Constraints From the Measurements of Baryon Acoustic Oscillations

Jiaxi Yu, Daniel Felipe Forero Sanchez, Antoine Philippe Jacques Rocher

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-alpha forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI ...

IOP Publishing Ltd2025

Euclid preparation XXXVI. Modelling the weak lensing angular power spectrum

Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Gianluca Castignani, Austin Chandler Peel

This work considers which higher order modeling e ffects on the cosmic shear angular power spectra must be taken into account for Euclid. We identified the relevant terms and quantified their individual and cumulative impact on the cosmological parameter i ...

Edp Sciences S A2024

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

Minh Hieu Lê

Semi-supervised semantic segmentation methods leverage unlabeled data by pseudo-labeling them. Thus the success of these methods hinges on the reliability of the pseudo-labels. Existing methods mostly choose high-confidence pixels in an effort to avoid err ...

Springer Science and Business Media Deutschland GmbH2025