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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25Cited by 0

Rheasus/qmi-repo: v2.0.3 — Archival release (revised manuscript, cluster-aware statistics)

Gorkem Yilmaz

Code, run specifications, and per-run artifacts for 'A Cross-Domain Empirical Benchmark of Quantum-Inspired and Classical Optimization Algorithms for Machine Learning'. All main-text tables and figures of the paper regenerate programmatically from this tree (v2/codes/analysis/).

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

Rheasus/qmi-repo: v2.0.6 — Archival release (revised manuscript)

Gorkem Yilmaz

Code, run specifications, and per-run artifacts for 'A Cross-Domain Empirical Benchmark of Quantum-Inspired and Classical Optimization Algorithms for Machine Learning'. The main-text result tables and generated figures of the paper regenerate programmatically from this tree (v2/c…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

TIDE: Turbulent Incompressible DNS Ensembles - datasheet, code snapshot, and benchmark split manifest

Yilong Dai, Yiming Sun, Yuehua Chen, Shengyu Chen, Peyman Givi, Xiaowei Jia, et al.

TIDE is a physically diverse 3D turbulence benchmark dataset: 15 configurations of the same incompressible Navier-Stokes system along eight physics axes (forced isotropic, extended physics, free decay), each shipping 8-16 fully independent realizations at 256^3 in fp64 (134 traje…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

Leakage-Safe Evaluation of Sensor-Failure Robustness in Dynamic Gas Mixture Quantification

Bakti Dwi Waluyo, Muhammad Aulia Rahman Sembiring

This repository contains the complete execution pipeline for the study: "Leakage-Safe Evaluation of Stochastic Channel Masking for Sensor-Failure Robustness in Dynamic Gas Mixture Quantification." The code provides an end-to-end reproducible workflow for processing the UCI Gas Se…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Detection Depth and Distributed Trust in AI-Based IoT Intrusion Detection: A Systematic Analysis

Gilbert Aimufua, Hashim Abdul Isah

Blockchain-integrated deep learning intrusion detection systems for the Internet of Things have attracted growing research attention, yet the relationship between detection depth and blockchain trust scope in these architectures has not been examined systematically. This analysis…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

ML Precipitation Prediction Framework

Manuel Ricardo Pérez Reyes, Marco Javier Suárez Barón, Oscar García-Cabrejo, Octavio Castillo-Reyes

Open-source framework for monthly precipitation prediction in mountainous areas using hybrid deep learning. The framework provides reference implementations for eight model families and a uniform training, evaluation, and benchmarking pipeline: ConvLSTM family — baseline, bidirec…

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