Publications related to Ground-based image deconvolution with Swin Transformer UNet

Related publications (25)

Euclid preparation: LXXII. Three-dimensional galaxy clustering in configuration space: Two-point correlation function estimation

The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of a ...

2025

COSMOS-Web: The Role of Galaxy Interactions and Disk Instabilities in Producing Starbursts at z < 4

Pascale Jablonka, Michaela Hirschmann

We study of the role of galaxy-galaxy interactions and disk instabilities in producing starburst activity in galaxies out to z = 4. For this, we use a sample of 387 galaxies with robust total star formation rate measurements from Herschel, gas masses from ...

2025

HOD-dependent systematics for luminous red galaxies in the DESI 2024 BAO analysis

Jiaxi Yu, Antoine Philippe Jacques Rocher

In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper f ...

IOP Publishing Ltd2025

An Analysis of Model Robustness across Concurrent Distribution Shifts

Myeongho Jeon, Shuqing Teresa Yeo

Machine learning models, meticulously optimized for source data, often fail to predict target data when faced with distribution shifts (DSs). Previous benchmarking studies, though extensive, have mainly focused on simple DSs. Recognizing that DSs often occ ...

2025

Automated Multicohort Mobility Assessment with an Instrumented L-test (iL-test)

Anisoara Ionescu

The L-test is a performance-based measure to assess balance and mobility. Currently, the primary outcome from this test is the time required to finish it. In this study we present the instrumented L-test (iL-test), an L-test wherein mobility is evaluated b ...

2025

Learning Algorithms in the Limit

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov

This paper studies the problem of learning computable functions in the limit by extending Gold's inductive inference framework to incorporate computational observations and restricted input sources. Complimentary to the traditional Input-Output Observation ...

2025

Temporally-Consistent Surface Reconstruction Using Metrically-Consistent Atlases

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík

We propose a method for unsupervised reconstruction of a temporally-consistent sequence of surfaces from a sequence of time-evolving point clouds. It yields dense and semantically meaningful correspondences between frames. We represent the reconstructed su ...

2025

Low-Rank Adaptation for Transformers in Dynamic Hand Gesture Recognition Using High-Density Surface Electromyography

Xingce Bao

Dynamic hand gesture recognition (HGR) is critical for real-time prosthetics and neural robotics applications, where high-density surface electromyography (HD-sEMG) signals provide valuable insights into muscle activity. However, adapting machine learning ...

IEEE2025

Dwarf galaxies in the MATLAS Survey: Hubble Space Telescope observations of the globular cluster systems of 74 ultra-diffuse galaxies

Oliver Müller

Ultra-diffuse galaxies (UDGs), characterised by their low surface brightness and large physical size, constitute a subclass of dwarf galaxies that challenge our current understanding of galaxy formation and evolution. In this paper, we probe the properties ...

2024

Advances in Algorithms for Sampling, Optimization and Inference in Disordered Systems

Giovanni Piccioli

This thesis focuses on the development of advanced algorithmic techniques, primarily Markov Chain Monte Carlo (MCMC) methods, and message passing algorithms, to tackle high-dimensional optimization and inference problems. The algorithms used have a probabi ...

EPFL2024

Enhancing spatial resolution in MÖNCH for electron microscopy via deep learning

Benjamin Bejar Haro, Luis Felipe Barba Flores, Carl Pierre Jacques Remlinger

However, their use in imaging applications has been limited by their relatively large pixel size (≥ 55 μm) and high-energy (>80 keV) electrons scattering over multiple pixels in the sensor layer. To realize the full potential of fast, radiation-hard HPDs a ...

2024

Neural decoding and feature selection methods for closed-loop control of avoidance behavior

Mahsa Shoaran, Jinhan Liu

Objective. Many psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local fi ...

IOP Publishing2024

Multi-Label Generalized Zero Shot Chest X-Ray Classification by Combining Image-Text Information With Feature Disentanglement

Seyedbehzad Bozorgtabar

In fully supervised learning-based medical image classification, the robustness of a trained model depends on its exposure to various disease classes. Generalized Zero Shot Learning (GZSL) aims to predict both seen and novel unseen classes. While most GZSL ...

Institute of Electrical and Electronics Engineers2024

Rock Glacier Kinematics in the Valles Calchaquíes Region, Northwestern Argentina, From Multi-Temporal Aerial and Satellite Imagery (1968-2023)

Sebastian Humberto Vivero Andrade

In semiarid mountain ranges, rock glaciers constitute an important part of the periglacial environment. However, quantitative data on the state of rock glacier activity remain scarce. Here, we derive kinematic information on rock glaciers located in the Va ...

WILEY2024

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations

Volkan Cevher, Grigorios Chrysos, Igor Krawczuk, Justin Samuel Deschenaux

Denoising Diffusion Probabilistic Models (DDPMs) exhibit remarkable capabilities in image generation, with studies suggesting that they can generalize by composing latent factors learned from the training data. In this work, we go further and study DDPMs t ...

2024

Euclid preparation: XLIV. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-ΛCDM models

Frédéric Courbin, Georges Meylan

Context. The Euclid space satellite mission will measure the large-scale clustering of galaxies at an unprecedented precision, providing a unique probe of modifications to the ?CDM model. Aims. We investigated the approximations needed to efficiently predi ...

2024

Learning Outcomes, Benefits, and Challenges of International Research Experiences for Students (IRES): An Exploratory Study of an IRES Program in China

Yousef Jalali

Despite the increasing number of international programs targeting students’ learning of research and intercultural skills, there has been limited holistic investigation of students’ experiences employing both qualitative and quantitative methods. In this s ...

University of Rhode Island2024

Optimal performance of Graph Convolutional Networks on the Contextual Stochastic Block Model

Patrick Thiran, Guillaume Cyprien Dalle

For Graph Neural Networks, oversmoothing denotes the homogenization of vertex embeddings as the number of layers increases. To better understand this phenomenon, we study community detection with a linearized Graph Convolutional Network on the Contextual S ...

2024

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields: Processed data and trained models

Mathieu Salzmann, Alexander Mathis, Chen Zhao, Haozhe Qi

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024 Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis. Affiliation: EPFL Date: June, 2024 Link to the CVPR article: https://openaccess.thecvf.com/conte ...

Zenodo2024

Tip of the Red Giant Branch Distances with JWST. II. I-band Measurements in a Sample of Hosts of 10 Type Ia Supernova Match HST Cepheids

Richard Irving Anderson

The Hubble Tension, a >5σ discrepancy between direct and indirect measurements of the Hubble constant (H 0), has persisted for a decade and motivated intense scrutiny of the paths used to infer H 0. Comparing independently derived distances for a set of ga ...

2024