output
20202026
most citedGeometry-preserving Lie Group Integrators For Differential Equations On The Manifold Of Symmetric Positive Definite Matrices

1 citations

18 papers

cond-mat.mtrl-sci2026

Lithography-free patterning of SrTiO-based two-dimensional electron gases using direct atomic layer processing

Anshu Gupta, Karolis Parfeniukas, Amit Chanda +5

We present a scalable and lithography-free strategy for the realization of a two-dimensional electron gas (2DEG) in TiO-patterned SrTiO (100) via Al deposition using magnet…

cs.MA2026

LOTUSim: Multi-Domain Simulator for Marine Robotics

Cédric Buche, Juliette Grosset, Hélène Lechêne +4

Simulation is essential for maritime robotics, supporting operator training, mission rehearsal, and human-vehicle interaction in environments where real-world testing is costly or…

eess.IV2026

A Hybrid Physical--Digital Framework for Annotated Fracture Reduction Data Evaluated using Clinically Relevant 3D metrics

Basile Longo, Paul-Emmanuel Edeline, Hoel Letissier +4

A major bottleneck in Computer-Assisted Preoperative Planning (CAPP) for fracture reduction is the limited availability of annotated data. While annotated datasets are now availabl…

quant-ph2026

Energy-time attack on detectors in quantum key distribution

Konstantin Zaitsev, Vladimir Bizin, Dmitriy Kuzmin +1

Quantum key distribution is unbreakable in theory but may be hacked via imperfections in its hardware implementations. While many imperfections have been mitigated by countermeasur…

cs.LG2026

Discovering Data Manifold Geometry through Geometric Properties

David Vigouroux, Lucas Drumetz, Ronan Fablet +1

A prevailing paradigm in modern representation learning is the map-first approach, in which a representation map is learned from reconstruction, embedding, or task objectives. At t…

eess.SP2026

Majorization-Minimization Networks for Inverse Problems: An Application to EEG Imaging

Le Minh Triet Tran, Sarah Reynaud, Ronan Fablet +3

Inverse problems are often ill-posed and require optimization schemes with strong stability and convergence guarantees. While learning-based approaches such as deep unrolling and m…

physics.optics2025

Thermal scanning probe lithography for fabrication of perforated metallic films

Paloma E S Pellegrini, Francisco T Orlandini, Silvia V G Nista +3

Thermal scanning probe lithography offers high resolution and versatility, making it a promising alternative for fabricating photonic devices. Here, we introduce a new method that…

math.PR2025

Elementary Tail Bounds on the Hypergeometric Distribution

Vaisakh Mannalath, Víctor Zapatero, Marcos Curty

We use a simple method to derive two concentration bounds on the hypergeometric distribution. Comparison with existing results illustrates the advantage of these bounds across diff…

eess.SP2025

Application of Quaternions to Obtain Analytic Solutions to Systems of Polarization Components

Michael G. Taylor

This paper describes the passage of light through a system of waveplates mathematically in terms of quaternions, an extension of the complex numbers, instead of the more usual Jone…

cs.RO2024

Leveraging Event Streams with Deep Reinforcement Learning for End-to-End UAV Tracking

Ala Souissi, Hajer Fradi, Panagiotis Papadakis

In this paper, we present our proposed approach for active tracking to increase the autonomy of Unmanned Aerial Vehicles (UAVs) using event cameras, low-energy imaging sensors that…

cs.RO2024

Collision and Obstacle Avoidance for Industrial Autonomous Vehicles -- Simulation and Experimentation Based on a Cooperative Approach

Juliette Grosset, Alain-Jérôme Fougères, M Djoko-Kouam +2

One of the challenges of Industry 4.0, is to determine and optimize the flow of data, products and materials in manufacturing companies. To realize these challenges, many solutions…

cs.LG2024

Feature Expansion and enhanced Compression for Class Incremental Learning

Quentin Ferdinand, Gilles Le Chenadec, Benoit Clement +2

Class incremental learning consists in training discriminative models to classify an increasing number of classes over time. However, doing so using only the newly added class data…

cs.LG2023

Goal Space Abstraction in Hierarchical Reinforcement Learning via Reachability Analysis

Mehdi Zadem, Sergio Mover, Sao Mai Nguyen

Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. H…

cs.LO2023

A more general categorical framework for congruence of applicative bisimilarity

Tom Hirschowitz, Ambroise Lafont

We prove a general congruence result for bisimilarity in higher-order languages, which generalises previous work to languages specified by a labelled transition system in which pro…

cs.LG2023

Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data

Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2

Over the last few years, several works have proposed deep learning architectures to learn dynamical systems from observation data with no or little knowledge of the underlying phys…

eess.SP2022★ 1 cited

Geometry-preserving Lie Group Integrators For Differential Equations On The Manifold Of Symmetric Positive Definite Matrices

Lucas Drumetz, Alexandre Reiffers-Masson, Naoufal El Bekri +1

In many applications, one encounters signals that lie on manifolds rather than a Euclidean space. In particular, covariance matrices are examples of ubiquitous mathematical objects…

cs.AI2022

Online Multi-Agent Decentralized Byzantine-robust Gradient Estimation

Alexandre Reiffers-Masson, Isabel Amigo

In this paper, we propose an iterative scheme for distributed Byzantineresilient estimation of a gradient associated with a black-box model. Our algorithm is based on simultaneous…

cs.NI2020

Low-Complexity Angle-Domain MIMO NOMA System with partial channel state information for MmWave Communications *

Israa Khaled, Charlotte Langlais, Ammar Falou +2

In millimeter-wave communication, digital beamsteering (DBS), only based on the user direction, is a promising angle-domain multi-antenna technique to mitigate the severe path loss…