Papers
Research papers from arXiv and related sources
On the Transfer of Collinearity to Computer Vision
Collinearity is a visual perception phenomenon in the human brain that amplifies spatially aligned edges arranged along a straight line. However, it is vague for which purpose humans might have thi...
Frederik Beuth, Danny Kowerko
HistoAtlas: A Pan-Cancer Morphology Atlas Linking Histomics to Molecular Programs and Clinical Outcomes
We present HistoAtlas, a pan-cancer computational atlas that extracts 38 interpretable histomic features from 6,745 diagnostic H&E slides across 21 TCGA cancer types and systematically links every ...
Pierre-Antoine Bannier
Splitting horizontal and vertical polynomial order in a compatible finite element discretisation for numerical weather prediction
The accurate and efficient representation of atmospheric dynamics remains a central challenge in numerical weather prediction. A particular difficulty arises from the strong anisotropy of the atmos...
Daniel Witt, Thomas Bendall, Jemma Shipton
Deep Learning-Driven Black-Box Doherty Power Amplifier with Pixelated Output Combiner and Extended Efficiency Range
This article presents a deep learning-driven inverse design methodology for Doherty power amplifiers (PA) with multi-port pixelated output combiner networks. A deep convolutional neural network (CN...
Han Zhou, Haojie Chang, David Widen
Applicability of Radiowave Anechoic Chambers for Acoustic Free-Field Measurements on the Example of the Chamber at ITMO University
Acoustic anechoic chambers allow free-field measurements required for the verification of effects under investigation and for the characterization of developing devices. However, the construction o...
Farid Bikmukhametov, Ksenia Razrezova, Roman Smolnitsky, Yuri Shchelokov, Nikolay Kanev, Mariia K...
SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation
In light of globalized hardware supply chains, the assurance of hardware components has gained significant interest, particularly in cryptographic applications and high-stakes scenarios. Identifyin...
Christian Gehrmann, Jonas Ricker, Simon Damm, Deruo Cheng, Julian Speith, Yiqiong Shi, Asja Fisch...
A Pin-Array Structured Climbing Robot for Stable Locomotion on Steep Rocky Terrain
Climbing robots face significant challenges when navigating unstructured environments, where reliable attachment to irregular surfaces is critical. We present a novel mobile climbing robot equipped...
Keita Nagaoka, Kentaro Uno, Kazuya Yoshida
Testing the Coexistence of Dark Energy and Dark Matter with Late-time Observational Data
We investigate the viability of a cosmological scenario with interacting dark sector, which can describe the coexistence between dark energy and dark matter. The model possesses an analytical solut...
Shambel Sahlu, Andronikos Paliathanasis, Genly Leon, Amare Abebe
Estimation and Hypothesis Testing of Fixed Effects Models-Based Uncertainty for Factor Designs
To analyze the uncertain data frequently encountered in practice, this paper proposes novel fixed-effects models that incorporate an uncertain measure to investigate variables of interest and nuisa...
Fan Zhang, Zhiming Li
Consensus in Multi-Agent Systems with Uniform and Nonuniform Communication Delays
This paper analyzes consensus in multi-agent systems under uniform and nonuniform communication delays, a key challenge in distributed coordination with applications to robotic swarms. It investiga...
Shokoufeh Naderi, Maude Blondin, Sébastien Roy
Monte Carlo sampling from a projected entangled-pair state in simulations of quantum annealing in the three dimensional random Ising model
Quantum annealing with the D-Wave Advantage system in the random Ising model on a cubic lattice is simulated using a three-dimensional (3D) tensor network. The Hamiltonian is driven across a quantu...
Jacek Dziarmaga
When Rolling Gets Weird: A Curved-Link Tensegrity Robot for Non-Intuitive Behavior
Conventional mobile tensegrity robots constructed with straight links offer mobility at the cost of locomotion speed. While spherical robots provide highly effective rolling behavior, they often la...
Lauren Ervin, Harish Bezawada, Vishesh Vikas
From the Inside Out: Progressive Distribution Refinement for Confidence Calibration
Leveraging the model's internal information as the self-reward signal in Reinforcement Learning (RL) has received extensive attention due to its label-free nature. While prior works have made signi...
Xizhong Yang, Yinan Xia, Huiming Wang, Mofei Song
Achieving Sub-Zeptonewton Force Sensitivity and Spin-Motion Entanglement in Levitated Diamond via Pulsed Backaction Evasion
We propose a system to achieve sub-zeptonewton force sensing and robust spin-mechanical entanglement in a levitated diamond system. By coupling a Nitrogen-Vacancy (NV) center spin to the motion of ...
Gayathrini Premawardhana, Jonathan Beaumariage, M. V. Gurudev Dutt, David Pekker, Thomas Purdy, J...
A Novel Approach for Fault Detection and Failure Analysis of CMOS Copper Metal Stacks
For the Inner Tracking System 3 (ITS3) upgrade, the ALICE experiment at CERN requires monolithic active pixel sensors of dimensions up to 97~mm$\,\times\,$266~mm, occupying a large fraction of a 30...
Gregor Hieronymus Eberwein, Gianluca Aglieri Rinella, Daniela Bortoletto, Szymon Bugiel, Francesc...
Capability-Guided Compression: Toward Interpretability-Aware Budget Allocation for Large Language Models
Large language model compression has made substantial progress through pruning, quantization, and low-rank decomposition, yet a fundamental limitation persists across all existing methods: compress...
Rishaank Gupta
High-Precision Photometry with a scientific CMOS Camera: II On-Sky Testing of the Marana camera at the NGTS facility
Modern scientific CMOS cameras offer very fast readout speeds and low read noise. In this study, we evaluate the performance of the Andor Marana CMOS camera through on-sky testing carried out at th...
Ioannis Apergis, Daniel Bayliss, Paul Chote, James McCormac, Peter J. Wheatley, Morgan A. Mitchel...
Decoding the Critique Mechanism in Large Reasoning Models
Large Reasoning Models (LRMs) exhibit backtracking and self-verification mechanisms that enable them to revise intermediate steps and reach correct solutions, yielding strong performance on complex...
Hoang Phan, Quang H. Nguyen, Hung T. Q. Le, Xiusi Chen, Heng Ji, Khoa D. Doan
Parameter Optimization of Domain-Wall Fermion using Machine Learning
We study a parameter optimization of domain-wall fermions to improve chiral symmetry based on machine learning. Domain-wall fermions involve coefficients along the fifth dimension, which can be tre...
Shunsuke Yasunaga, Kenta Yoshimura, Akio Tomiya, Yuki Nagai
A Kernel Two-Sample Test Invariant under Group Action with Applications to Functional Data
We introduce a kernel-based two-sample test for comparing probability distributions up to group actions. Our construction yields invariant kernels for locally compact $σ$-compact groups and extends...
Madison Giacofci, Anouar Meynaoui, Alex Podgorny