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51 to 60 of 21,100 Results
test_model_wrapper.py
May 22, 2026 - Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics
Python Source Code - 4.8 KB - MD5: d0a9867c442111e30c0e12e53092ca8e
test_predict_cli.py
May 22, 2026 - Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics
Python Source Code - 9.1 KB - MD5: 49c9616d14d08a836de518a167eeacf0
test_pretrained_validation.py
May 22, 2026 - Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics
Python Source Code - 6.2 KB - MD5: 142b8a6fe1fd2fcc3682f70c93812076
test_randomized_models.py
May 22, 2026 - Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics
Python Source Code - 11.9 KB - MD5: 9588c213a051bf937b266de6312ed302
utils.py
May 22, 2026 - Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics
Python Source Code - 1023 B - MD5: 7b087deadf47c713a62105c64888140a
utils.py
May 22, 2026 - Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics
Python Source Code - 1023 B - MD5: 7b087deadf47c713a62105c64888140a
Studying Dynamical Systems for Intelligible Modeling and Unconventional Computing(Universität Stuttgart)
May 20, 2026PN 6
We investigate computation through the lens of dynamical systems, unifying physical processes and machine learning. By treating both hardware and algorithms as evolving dynamical systems, we leverage natural physical dynamics - such as relaxation to stable states and phase transitions - as a foundation for robust, efficient computation. Our work sh...
Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
May 11, 2026 - PN 3-11
Korn, Viktoria Helena; Pluhackova, Kristyna, 2026, "Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"", https://doi.org/10.18419/DARUS-5682, DaRUS, V2
GROMACS simulation files, input and final structures for CHARMM36m MD simulations including our refined parameters for phosphorylated serine in 3 different protonation states. The directory charmm36-jul22mod.ff contains our refined parameters.
charmm36-jul2022mod.ff.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 1.1 MB - MD5: e5e758a42a7a04a3af52bd2a3746f599
Ready-to-use CHARMM36m force field with our parameters for phosphorylated aminoacids
charmm_toppar_mod.zip
May 11, 2026 - Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"
ZIP Archive - 1.4 MB - MD5: 10d788673880f41321b528dd43b8b042
Patched CHARMM36m force field files for CHARMM with our parameters
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