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/codes/analysis/), with the labelled exceptions stated in the manuscript: the appendix tables retain v1 values verbatim, and in the QPSO cost table the LSTM Adam reference times are v1 measurements while the AG News row is a projection.
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/).
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…
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…
This record contains the complete anonymized reproducibility archive for the manuscript “Risk-averse optimization of Internet of Things sensor placement in semiconductor wastewater networks: A mass-balanced simulation and Monte Carlo framework.” The archive includes three reconst…
Vector Network Idealism (VNI) v1.4: A Relational Quantum-Informational Field Theory of Emerging Spacetime and Gravitation Overview: Vector Network Idealism (VNI) v1.4 represents a major theoretical milestone in the VNI framework, formally establishing 3+1-dimensional Riemannian s…
This archive contains the analysis code, the predictor dictionary, and the retrained primary model objects underlying the manuscript "Interpretable machine-learning risk stratification at the time of diagnosis for 3-year mortality in de novo metastatic prostate cancer: developmen…