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61 to 70 of 264 Results
UA-molecule.xtc
Oct 16, 2024 - Scripts and data for "Calculation of 1H-NMR relaxation rates from a model united-atom alkanes using reverse coarse-graining"
Unknown - 53.2 KB - MD5: ea602a9ba6df1280956e0b606fb4f80a
Trajectory sample
UA.tpr
Oct 16, 2024 - Scripts and data for "Calculation of 1H-NMR relaxation rates from a model united-atom alkanes using reverse coarse-graining"
Unknown - 18.2 KB - MD5: 03d56ca470f426b290a01294bf227879
Trajectory sample
UA.xtc
Oct 16, 2024 - Scripts and data for "Calculation of 1H-NMR relaxation rates from a model united-atom alkanes using reverse coarse-graining"
Unknown - 56.2 KB - MD5: e01009724988b3c1d3347d74367ef824
Trajectory sample
utilities.py
Oct 16, 2024 - Scripts and data for "Calculation of 1H-NMR relaxation rates from a model united-atom alkanes using reverse coarse-graining"
Python Source Code - 17.0 KB - MD5: d295794f87711f8f50f19d1f72f3d497
Python script for converting trajectories
Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Aug 2, 2024
Tovey, Samuel; Lohrmann, Christoph; Holm, Christian, 2024, "Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning", https://doi.org/10.18419/DARUS-4431, DaRUS, V1
Scripts used in the experiments and analysis presented in the paper.
chemotaxis-analysis-checkpoint.ipynb
Aug 2, 2024 - Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Jupyter Notebook - 137.7 KB - MD5: 65d2b4daf4410f698dbbe0be5187240f
find-center-deployment.py
Aug 2, 2024 - Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Python Source Code - 4.3 KB - MD5: 45a4a851a5fda227676dad2aeb6f253f
find-center-deployment.py
Aug 2, 2024 - Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Python Source Code - 5.1 KB - MD5: ae113c6ce9c13b934600c7324dd09ea2
find-center-deployment.py
Aug 2, 2024 - Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Python Source Code - 5.1 KB - MD5: e3feff2ecd3c657ffbc164409a59cbf9
find-center-rl.py
Aug 2, 2024 - Replication Data for: Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Python Source Code - 7.6 KB - MD5: 5813873213ca1c0277d4c2b195600fe0
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