Tootfinder

Secure Blind Graph Signal Recovery and Adversary Detection Using Smoothness Maximization
Mahdi Shamsi, Hadi Zayyani, Hasan Abu Hilal, Mohammad Salman
https://arxiv.org/abs/2509.14449

Secure Blind Graph Signal Recovery and Adversary Detection Using Smoothness Maximization
In this letter, we propose a secure blind Graph Signal Recovery (GSR) algorithm that can detect adversary nodes. Some unknown adversaries are assumed to be injecting false data at their respective nodes in the graph. The number and location of adversaries are not known in advance and the goal is to recover the graph signal in the presence of measurement noise and False Data Injection (FDI) caused by the adversaries. Consequently, the proposed algorithm would be a perfect candidate to solve this…

How Bad Is Forming Your Own Multidimensional Opinion?
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz, Danny Mittal, Alipasha Montaseri
https://arxiv.org/abs/2509.14411

How Bad Is Forming Your Own Multidimensional Opinion?
Understanding the formation of opinions on interconnected topics within social networks is of significant importance. It offers insights into collective behavior and decision-making, with applications in Graph Neural Networks. Existing models propose that individuals form opinions based on a weighted average of their peers' opinions and their own beliefs. This averaging process, viewed as a best-response game, can be seen as an individual minimizing disagreements with peers, defined by a quadra…

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- Advanced Physics-Informed Neural Network with Residuals for Solving Complex Integral Equations
Mahdi Movahedian Moghaddam, Kourosh Parand, Saeed Reza Kheradpisheh

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[1/8]:
- Deep Multimodal Subspace Clustering Networks
Mahdi Abavisani, Vishal M. Patel
ht…

Placeit! A Framework for Learning Robot Object Placement Skills
Amina Ferrad, Johann Huber, Fran\c{c}ois H\'el\'enon, Julien Gleyze, Mahdi Khoramshahi, St\'ephane Doncieux
https://arxiv.org/abs/2510.09267

Placeit! A Framework for Learning Robot Object Placement Skills
Robotics research has made significant strides in learning, yet mastering basic skills like object placement remains a fundamental challenge. A key bottleneck is the acquisition of large-scale, high-quality data, which is often a manual and laborious process. Inspired by Graspit!, a foundational work that used simulation to automatically generate dexterous grasp poses, we introduce Placeit!, an evolutionary-computation framework for generating valid placement positions for rigid objects. Placei…

HyCoVAD: A Hybrid SSL-LLM Model for Complex Video Anomaly Detection
Mohammad Mahdi Hemmatyar, Mahdi Jafari, Mohammad Amin Yousefi, Mohammad Reza Nemati, Mobin Azadani, Hamid Reza Rastad, Amirmohammad Akbari
https://arxiv.org/abs/2509.22544

HyCoVAD: A Hybrid SSL-LLM Model for Complex Video Anomaly Detection
Video anomaly detection (VAD) is crucial for intelligent surveillance, but a significant challenge lies in identifying complex anomalies, which are events defined by intricate relationships and temporal dependencies among multiple entities rather than by isolated actions. While self-supervised learning (SSL) methods effectively model low-level spatiotemporal patterns, they often struggle to grasp the semantic meaning of these interactions. Conversely, large language models (LLMs) offer powerful…

LATIS Data Release: $\sim4200$ Spectra of $z \sim 2-3$ Galaxies, Redshifts, and IGM Tomography Maps
Andrew B. Newman, Gwen C. Rudie, Guillermo A. Blanc, Daniel D. Kelson, Nima Chartab, Enrico Congiu, Victoria P\'erez, Mahdi Qezlou, Simeon Bird, Brian C. Lemaux, Olga Cucciati
https://arxiv.org/abs/2510.08815

LATIS Data Release: $\sim4200$ Spectra of $z \sim 2-3$ Galaxies, Redshifts, and IGM Tomography Maps
We present the data release of the Ly$α$ Tomography IMACS Survey (LATIS), one of the largest optical spectroscopic surveys of faint high-redshift galaxies. The survey provides 7408 optical spectra of candidate $z \sim 2-3$ galaxies and QSOs in the Canada-France-Hawaii Telescope Legacy Survey D1, D2 (COSMOS), and D4 fields. The $R \sim 1000$ spectra were obtained using the IMACS spectrograph at the Magellan Baade telescope, with typical integrations of 12 hr. From these spectra, we measured 557…

Measuring Innovation Patterns in Iran and Neighboring Countries: A Time Series Similarity Approach Using STL and Dynamic Time Warping
Mahdi Goldani
https://arxiv.org/abs/2510.10323

Measuring Innovation Patterns in Iran and Neighboring Countries: A Time Series Similarity Approach Using STL and Dynamic Time Warping
Innovation is becoming ever more pivotal to national development strategies but measuring and comparing innovation performance across nations is still a methodological challenges. This research devises a new time-series similarity method that integrates Seasonal-Trend decomposition (STL) with Fast Dynamic Time Warping (DTW) to examine Irans innovation trends by comparison with its regional peers. Owing to data availability constraints of Global Innovation Index data , research and development s…

Low Overhead Universal Quantum Computation with Triorthogonal Codes
Dawei Jiao, Mahdi Bayanifar, Alexei Ashikhmin, Olav Tirkkonen
https://arxiv.org/abs/2510.05708 https://

Low Overhead Universal Quantum Computation with Triorthogonal Codes
We explore the use of triorthogonal codes for universal fault-tolerant quantum computation and propose two methods to circumvent the Eastin-Knill theorem, which prohibits any single quantum error-correcting code from supporting both universality and a transversal gate set. First, we simplify the implementation of the logical Hadamard gate for triorthogonal codes by exploiting the fact that they have transversal controlled-Z (CZ) gates, resulting in a circuit with reduced overhead. Then, we intr…

Enhancing Automotive Security with a Hybrid Approach towards Universal Intrusion Detection System
Md Rezanur Islam, Mahdi Sahlabadi, Keunkyoung Kim, Kangbin Yim
https://arxiv.org/abs/2510.05824

Enhancing Automotive Security with a Hybrid Approach towards Universal Intrusion Detection System
Security measures are essential in the automotive industry to detect intrusions in-vehicle networks. However, developing a one-size-fits-all Intrusion Detection System (IDS) is challenging because each vehicle has unique data profiles. This is due to the complex and dynamic nature of the data generated by vehicles regarding their model, driving style, test environment, and firmware update. To address this issue, a universal IDS has been developed that can be applied to all types of vehicles wit…