Papers
Research papers from arXiv and related sources
Defect dependent dynamic nanoindentation hardness of copper up to 25 000 s-1
Metals exhibit an upturn in strength at strain rates of approximately 1000 s-1 - 3000 s-1, governed by rapid dislocation multiplication, interactions and storage. This phenomenon is strongly influe...
Hendrik Holz, Lalith Kumar Bhaskar, Tobias Brink, Dipali Sonowane, Gerhard Dehm, James P. Best, R...
On Channel Model to Bridge the Gap between MIMO Design and Performance Requirements in 3GPP
Accurate channel modeling has become critical for evaluating multiple-input multiple-output (MIMO) performance, especially as 5G standardization matures and efforts toward 6G begin. Recent studies ...
Lynda Berrah, Raphael Visoz, Didier Le Ruyet, Anvar Tukmanov, Axel Müeller, Alexander Hamilton, M...
Uniform-in-time concentration in two-layer neural networks via transportation inequalities
We quantify, uniformly over time and with high probability, the discrepancy between the predictions of a two-layer neural network trained by stochastic gradient descent (SGD) and their mean-field l...
Arnaud Guillin, Boris Nectoux, Paul Stos
Affine Correspondences in Stereo Vision: Theory, Practice, and Limitations
Affine transformations have been recently used for stereo vision. They can be exploited in various computer vision application, e.g., when estimating surface normals, homographies, fundamental and ...
Levente Hajder
Experimental realization and self-testing of semisymmetric informationally complete measurements via a one-dimensional photonic quantum walk
Generalized quantum measurements play a crucial role in quantum mechanics, and symmetric informationally complete positive operator-valued measurements (SIC POVMs) provide a powerful and flexible f...
Xu Xu, Han-Yu Cheng, Meng-Yun Ma, Chao-Jie Sun, Yan Wang, Li-Jiong Shen, Zhe Sun, Qi-Ping Su, Chu...
Learning Shortest Paths with Generative Flow Networks
In this paper, we present a novel learning framework for finding shortest paths in graphs utilizing Generative Flow Networks (GFlowNets). First, we examine theoretical properties of GFlowNets in no...
Nikita Morozov, Ian Maksimov, Daniil Tiapkin, Sergey Samsonov
Testing the isothermal Jeans model for self-interacting dark matter halos in the collapse phase
We benchmark the semi-analytical isothermal Jeans model against a high-resolution isolated N-body simulation that follows a self-interacting dark matter (SIDM) halo into deep core collapse. The mod...
Shubo Li, Moritz S. Fischer, Zixiang Jia, Fangzhou Jiang, Ran Li, Hai-Bo Yu
Distinguishing thermal and pseudothermal light by testing the Siegert relation
Thermal light, including blackbody radiation and spontaneous emission, exhibits photon bunching. Thermal light sources, however, typically yield low spectral densities, limiting their practical uti...
Xi Jie Yeo, Justin Yu Xiang Peh, Darren Ming Zhi Koh, Christian Kurtsiefer, Peng Kian Tan
DGNet: Discrete Green Networks for Data-Efficient Learning of Spatiotemporal PDEs
Spatiotemporal partial differential equations (PDEs) underpin a wide range of scientific and engineering applications. Neural PDE solvers offer a promising alternative to classical numerical method...
Yingjie Tan, Quanming Yao, Yaqing Wang
Modular Memory is the Key to Continual Learning Agents
Foundation models have transformed machine learning through large-scale pretraining and increased test-time compute. Despite surpassing human performance in several domains, these models remain fun...
Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov, Lucas Caccia, Antonio Carta, Laurent Char...
U-Net based particle localization in granular experiments: Accuracy limits and optimization
Identifying the positions of granular particles from experimental images is often complicated by their partial overlap in two dimensional projections. Uneven backgrounds and inhomogeneous illuminat...
Fahad Puthalath, Matthias Schröter, Nicoletta Sanvitale, Matthias Sperl, Peidong Yu
An Analysis of Multi-Task Architectures for the Hierarchic Multi-Label Problem of Vehicle Model and Make Classification
Most information in our world is organized hierarchically; however, many Deep Learning approaches do not leverage this semantically rich structure. Research suggests that human learning benefits fr...
Alexandru Manole, Laura Diosan
Action-Guided Attention for Video Action Anticipation
Anticipating future actions in videos is challenging, as the observed frames provide only evidence of past activities, requiring the inference of latent intentions to predict upcoming actions. Exis...
Tsung-Ming Tai, Sofia Casarin, Andrea Pilzer, Werner Nutt, Oswald Lanz
Numerical method for strongly variable-density flows at low Mach number: flame-sheet regularisation and a mass-flux immersed boundary method
A low-Mach-number flow, in the laminar regime, has intrinsically two characteristic spatial scales for a given time scale, or two characteristic temporal scales for a given spatial scale, and these...
Matheus P. Severino, Fernando F. Fachini, Elmer M. Gennaro, Daniel Rodríguez, Leandro F. Souza
Local Gaussian copula inference with structural breaks: testing dependence predictability
We propose a score test for dependence predictability in conditional copulas that is robust to temporal instabilities. Our semiparametric procedure accommodates flexible dynamics in the marginal pr...
Alexander Mayer, Tatsushi Oka, Dominik Wied
A spatial scan statistical for categorical, functional data
We have developed and tested a spatial scan statistic for categorical, functional data (CFSS) - a data structure within which current approaches cannot identify spatial clusters. Our methodology co...
Camille Frévent, Moustapha Sarr, Sophie Dabo-Niang
Power and Sample Size Calculations for Bayes Factors in two-arm clinical Phase II Trials with binary Endpoints
Bayesian sample size calculations in clinical trials usually rely on complex Monte Carlo simulations in practice. Obtaining bounds on Bayesian notions of the false-positive rate and power often lac...
Riko Kelter
A speciation simulation that partly passes open-endedness tests
One of the main goals of artificial life research is to recreate in artificial systems the trends for ever more complex and novel entities, interactions and processes that we see in Earth's biosphe...
Théo de Pinho, Lana Sinapayen
Predictive Importance Sampling Based Coverage Verification for Multi-UAV Trajectory Planning
Unmanned aerial vehicle (UAV) networks are emerging as a promising solution for ultra-reliable low-latency communication (URLLC) in next-generation wireless systems. A key challenge in millimeter w...
Snehashish Ghosh, Sasthi C. Ghosh
$\mathcal{H}$-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity
We present $\mathcal{H}\mathtt{-EFTCAMB}$, the official successor to $\mathtt{EFTCAMB}$. The original $\mathtt{EFTCAMB}$ is designed as a consistent and numerically stable implementation of the eff...
Gen Ye, Shijie Lin, Jiaming Pan, Dani de Boe, Stan Verhoeve, Marco Raveri, Bin Hu, Noemi Fruscian...