Publications associées à On the Convergence Speed of Spatially Coupled LDPC Ensembles

Publications associées (28)

Toward Universal Belief Propagation Decoding for Short Binary Block Codes

Andreas Peter Burg, Yifei Shen, Yuqing Ren

Belief propagation (BP) decoding has been recognized for its capacity-approaching performance and high throughput when decoding long low-density parity-check (LDPC) codes. However, the application of BP decoding for short codes is hindered by dense parity- ...

2025

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

Reka Inovan

Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

EPFL2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields

Farhad Rachidi-Haeri, Marcos Rubinstein, Nicolas Mora Parra, Hamidreza Karami, Elias Per Joachim Le Boudec

Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...

2024

Full-F turbulent simulation in a linear plasma device using a gyro-moment approach

Paolo Ricci, Baptiste Jimmy Frei

Simulations of plasma turbulence in a linear plasma device configuration are presented. These simulations are based on a simplified version of the gyrokinetic (GK) model proposed by Frei et al. [J. Plasma Phys. 86, 905860205 (2020)], where the full-F distr ...

Aip Publishing2024

Effects of Hyporheic Exchange and Settlement on the Particle Size Distribution of Colloids

David Andrew Barry, Qihao Jiang

Colloid particle size plays an important role in contaminant adsorption and clogging in the hyporheic zone, but it remains unclear how the particle size changes during the transport of colloids. This study investigated the variation of the particle size of ...

Springer2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Elsevier Science Sa2024

A story of two transitions: From adhesive to abrasive wear and from ductile to brittle regime

Jean-François Molinari, Sacha Zenon Wattel

Atomistic simulations performed with a family of model potential with tunable hardness have proven to be a great tool for advancing the understanding of wear processes at the asperity level. They have been instrumental in finding a critical length scale, w ...

2024

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

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Silvestro Micera

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

Ieee-Inst Electrical Electronics Engineers Inc2024

White adipose tissue distribution and amount are associated with increased white matter connectivity

Jean-Philippe Thiran, Gabriel Girard, Elda Fischi Gomez, Philipp Johannes Koch

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a ...

Wiley2024

The phase-space distribution of the M 81 satellite system

Oliver Müller, Nick Heesters

The spatial distribution of dwarf galaxies around their host galaxies is a critical test for the standard model of cosmology because it probes the dynamics of dark matter halos and is independent of the internal baryonic processes of galaxies. Comoving pla ...

Edp Sciences S A2024

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Yuejiang Liu

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

EPFL2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

swissALPS: a Dataset for Imbalanced Land Cover Mapping in Alpine Regions

Valérie Zermatten

Our dataset consists of very high-resolution aerial images (50cm) and a digital elevation model (50cm) that covers approx. 2300 km2 of land above 2000m altitude in the southwestern part of Switzerland. Our land cover labels focus on alpine land cover that ...

IEEE DataPort2023

Validation of GBS plasma turbulence simulation of the TJ-K stellarator

Paolo Ricci, Joaquim Loizu Cisquella

We present a validation of a three-dimensional, two-fluid simulation of plasma turbulence in the TJ-K stellarator, a low temperature plasma experiment ideally suited for turbulence measurements. The simulation is carried out by the GBS code, recently adapt ...

IOP Publishing Ltd2023

Functional data analysis with rough sample paths?

Victor Panaretos, Neda Mohammadi Jouzdani

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

TAYLOR & FRANCIS LTD2024

Gyrokinetic simulations of plasma turbulence in a Z-pinch using a moment-based approach and advanced collision operators

Paolo Ricci, Baptiste Jimmy Frei, Antoine Cyril David Hoffmann

The first nonlinear gyrokinetic simulations obtained using a moment approach based on the Hermite-Laguerre decomposition of the distribution function are presented, implementing advanced models for the collision operator. Turbulence in a two-dimensional Z- ...

Cambridge University Press2023