Dataset for Transformers to Predict the Applicability of Symbolic Integration Routines

This is the version related to the publication

Supporting code for the Tereso del Río Almajano's Thesis titled "Heuristics and Machine Learning to Improve Symbolic Computation Algorithms: Speeding Up Cylindrical Algebraic Decomposition"

This upload contains the dataset and code used throught Tereso del Río Almajano's thesis titled "Heuristics and Machine Learning to Improve Symbolic Computation Algorithms: Speeding Up Cylindrical Algebraic Decomposition" to evaluate the different strategies presented to choose the variable ordering. Moreover, this code also generates multiple figures and tables included in the thesis

CoVaRR-NET/duotang: Release for Zenodo Archive

Scripts and data for the CoVaRR-Net Pillar 6 noteboo

Computing solubility and thermodynamic properties of H2O2 in water

The input files used for GROMACS and BRICK software in this work has been uploaded. The dataset contains .itp files for the H2O2 forcefields used and the .mdp file used for a NPT run on aqueous H2O2 solution. GROMACS was used to determine the densities, viscosities and diffusion coefficients of H2O2 in water. Also, BRICK input files (forcefield.in, settings.in, topology.in, H2O2, water, restart.in and weightfunction.in) has been uploaded. BRICK was used to calculate the solubility (Henry coefficient) of H2O2 in water