Loading...
Loading...
Mathematical datasets, statistical benchmarks, probability, optimization, operations research
3,061 datasets
Davis Logic V2 is an open-access reference dataset containing a real-time 2D spatial matrix convolution engine and an automated validation testbed. It was authored by Dr. Jamie Edward Davis and published on figshare in 2026. The dataset includes a C++ header file implementing a fixed-point algorithm and a verification script, with a total size of 2.4 KB.
Jamie Davis released this open-access reference dataset in 2026. It provides two infrastructure tools for the Davis Logic V2 bare-metal framework: a branchless acceleration-clipping saturation engine and a phase lead-lag compensation verification testbed. The dataset is a 4.7 KB text file licensed under CC BY 4.0.
Simulation results from 2026 demonstrate the SWEET inference serving system. The data, authored by Xiangchen Li and shared under CC-BY-4.0, likely contains metrics on time, power consumption, communication payload, and accuracy degradation from experiments co-optimizing model quantization and workload partitioning for edge devices.
A verification and visualization package designed to prove the structural safety and mathematical stability of the Davis Logic V2 framework under catastrophic hardware failures. The dataset includes automated C++ and Python tools for injecting faults and generating publication-ready graphics. It was authored by Jamie Davis and published on figshare in 2026.
Multiple files support heuristic optimization of electric vehicle charging to minimize overloading in low voltage grids. The data includes lognormally sampled hourly scenarios across 11 charging locations and normally distributed household electricity use scenarios from agent-based modeling. The dataset was created by Sajjad Haider of Technische Universität Dresden to support a related research article.
Statistical analysis of ionospheric correlation distances using multisource assimilation data, IGS VTEC data, and ionosonde data. The research was conducted by Lv Mingjie of Wuhan University. The results detail variations with local time, magnetic latitude, and season.
An academic paper by Mário J. de Oliveira of Universidade de São Paulo, published under an Open Access license. It presents a theoretical framework for describing systems out of thermodynamic equilibrium using stochastic dynamics. The work includes an extension to quantum systems and an example of an irreversible system in a nonequilibrium stationary state.
Johan Kwisthout from Leiden University discusses the challenge of modeling human cognition with Bayesian computations, which are often computationally intractable. The paper analyzes three candidate notions of 'approximation' suggested in cognitive science literature to transform intractable models into computationally plausible ones. It proposes using parameterized computational complexity analyses to derive tractable model variants.
A paper discussing the computational complexity of Bayesian models in cognitive science. Authored by Johan Kwisthout of Leiden University, it examines three candidate notions of approximation to make intractable Bayesian computations tractable for modeling human cognition.
Determinantal quantum Monte Carlo (DQMC) data sets for the extended Hubbard model on a square lattice at half filling. The data includes double occupancy, internal energy, antiferromagnetic structure factor, and charge density wave structure factor, computed for the Hubbard, U-V, and long-range Coulomb-Hubbard models at fixed U/t=1.9. The data was generated by Alexander Sushchyev of RWTH Aachen University using the ALF Code.
Experimental data from a study modeling leachate degradation via the solar photo-Fenton process. The dataset includes results from a fractional factorial design optimizing pH, solar radiation, H2O2, and Fe2+ concentrations, achieving an 88.7% chemical oxygen demand reduction. The research was conducted by Alessandro Sampaio Cavalcanti using leachate from Cachoeira Paulista-SP.
K. Ashwin Kumar from the University of Maryland, College Park presents a prototype runtime called Hone for executing Hadoop applications on multi-core, shared-memory machines. The dataset likely contains performance metrics comparing Hone's execution on a single server against Hadoop running in pseudo-distributed mode and on a 16-node cluster. The paper demonstrates that for datasets fitting into a single machine's memory, Hone can be substantially faster.
A wage dataset from the United States is included as supplemental material for a paper on uniform inference methods for conditional mode estimation. The paper, authored by Tao Zhang of Cornell University, develops two bootstrap methods for constructing confidence intervals around modal regression estimates derived from quantile regression. Simulation experiments and a real data analysis using this wage data demonstrate the finite-sample performance of the proposed inference methods.
Experimental data from a study optimizing lignin properties in green biorefineries. The dataset contains results from processing biomass under varying reactor temperature and P-factor conditions, with measured lignin yield and NMR-quantified structural properties. It was created by Joakim Löfgren of Aalto University for a 2022 manuscript.
A paper by Stephen B. Pope of Cornell University introduces stochastic Lagrangian models for turbulent flows. It describes basic models for Lagrangian velocity and composition, applied to dispersion from a line source and a lifted turbulent jet flame. The paper also discusses refinements to account for Reynolds-number effects and intermittency, using information from experiments and direct numerical simulations.
University of Edinburgh researcher Nicolò Mazzi provides Julia code for solving a power system investment planning problem over a 15-year time horizon. The code models twelve technologies, including six thermal units, three storage units, and three renewable generation units, and solves the problem using two Benders decomposition algorithms. The deterministic version has three decision nodes at present, 5 years, and 10 years, while the stochastic version models different future scenarios.
A glossary of terms used in toxicology, compiled primarily for scientists working in the field. It is a revision of the 1993 IUPAC glossary, incorporating new terms from a 2004 publication. The glossary includes definitions, explanatory notes, and three annexes covering abbreviations, international bodies, and carcinogenicity classifications.
Giorgio Paulon from The University of Texas at Austin developed a novel Bayesian model for analyzing adult tone learning. The method provides insights into how biologically interpretable model parameters evolve with learning and differ between performance groups. The dataset likely contains longitudinal experimental data from a multi-category decision-making paradigm.
A 2026 dataset by Qianqian Xu presents results from a multi-objective optimization framework for tunnel lining structures. The data likely contains design parameters and performance metrics for 2,400 configurations of Ultra-High Performance Concrete (UHPC) and ordinary concrete composite linings. It was published on figshare under a CC-BY-4.0 license.
Module 121 from the Davis Logic V2 project provides a zero-heap, real-time fractional delay line for embedded systems. The component implements a single-multiplier recursive allpass filter to achieve sub-sample phase shifts with a flat 0 dB gain response. It was authored by Jamie Davis and released under a CC BY 4.0 license.