1 to 10 of 206,544 Results
Jul 18, 2025
Krueger, Matteo; Berkemeier, Thomas, 2025, "Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'", https://doi.org/10.17617/3.GIKHJL, Edmond, V2
We propose a novel approach to predict saturation vapor pressures using group contribution-assisted graph convolutional neural networks (GC2NN), which use both, molecular descriptors like molar mass and functional group counts, as well as molecular graphs containing atom and bond features, as representations of molecular structure. Molecular graphs... |
Jul 18, 2025 -
Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'
Windows Executable - 182.2 MB -
MD5: da088f6eba8c69fc58c9b4bee119601c
Executable model application for Windows |
Jul 18, 2025 -
Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'
ZIP Archive - 91.3 KB -
MD5: 5613a4d3f5be177c05e84384c7e8dac0
Source code and example script |
Jul 18, 2025 -
Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'
ZIP Archive - 93.4 KB -
MD5: 0116a25cff204b0766be334a22a98774
Vapor pressure predictions from other methods for comparison (OHE-CNN, EPI-suite, SIMPOL, EVAPORATION) |
Jul 18, 2025 -
Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'
ZIP Archive - 2.1 MB -
MD5: ae72f51d8b1c6c03e6242a31db6fab11
Pre-processed input data and test sets |
Jul 18, 2025 -
Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'
ZIP Archive - 101.7 KB -
MD5: b597682e33826434d232dd24fe08daac
Original data sets (Naef, pubchem) |
Jul 18, 2025 -
Code and data for 'Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)'
ZIP Archive - 33.1 KB -
MD5: b2d2f9f36cb92f06d502f2a2d0f10e05
Test set predictions and errors of final models |
Jul 18, 2025
Kiss, Bernadett Nicolette; Keating, Luke; Jin, Tianyi; Badri-Spröwitz, Alexander, 2025, "EcoWalker robot setup documentation", https://doi.org/10.17617/3.LXYCXY, Edmond, V1
Instructions for reproducing the EcoWalker robot setup. |
Jul 18, 2025 -
EcoWalker robot setup documentation
Adobe PDF - 236.1 MB -
MD5: ac376940c0fa172d796434b509cde8dc
Setup instructions for the EcoWalker robot setup |
Jul 18, 2025
Wong, Anabelle, 2024, "Assessing the effect of social contact structure on the impact of pneumococcal conjugate vaccines", https://doi.org/10.17617/3.RIGYAK, Edmond, V3
This project uses a deterministic, age-structured, Susceptible-Colonized transmission model to investigate the effect of social contact structure on the dynamics of vaccine impact and serotype replacement following pneumococcal conjugate vaccines (PCVs). Please see README.md for more details. For contact matrices, this project uses the data publish... |