PN 6

SimTech EXC 2075 Project Network 6 "Machine learning for simulation"

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761 to 770 of 1,126 Results

task_execution.py Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3] Python Source Code - 15.4 KB - MD5: 385768bef9acf4b5405bc930cc990e4d
test_single_task.py Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3] Python Source Code - 2.4 KB - MD5: b4893fa0014897b750b992d9807f9ae8
train.py Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3] Python Source Code - 11.3 KB - MD5: a69a123b85169194526706ff1e028a4b
using_bmdal.ipynb Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3] Jupyter Notebook - 302.2 KB - MD5: 0da36bda03f90507caecfa194fd5517c
utils.py Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3] Python Source Code - 7.9 KB - MD5: b57773306e54beb8c92b46a41714ea5a
visualize_lcmd.py Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3] Python Source Code - 2.9 KB - MD5: 23e591945e30abfe03e5187ab6ae5d53
Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Feb 20, 2023 Zaverkin, Viktor; Holzmüller, David; Bonfirraro, Luca; Kästner, Johannes, 2023, "Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials", https://doi.org/10.18419/DARUS-3299, DaRUS, V1 Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach. Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found on GitLab. The data represents TensorFlow v2 checkpoints and stores the metadata for the checkpoint and parameters for the mo...
best_stats_ens.pkl Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 331 B - MD5: f542921bad95c295381dcffbcb89fb29
best_stats_ens.pkl Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 331 B - MD5: 65e911f618faf04d770aa16179cda6b4
best_stats_ens.pkl Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 216 B - MD5: e2244122360fe086d8aa430934e1034b

task_execution.py

Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]

Python Source Code - 15.4 KB -

test_single_task.py

Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]

Python Source Code - 2.4 KB -

train.py

Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]

Python Source Code - 11.3 KB -

using_bmdal.ipynb

Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]

Jupyter Notebook - 302.2 KB -

utils.py

Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]

Python Source Code - 7.9 KB -

visualize_lcmd.py

Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]

Python Source Code - 2.9 KB -

Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials

Feb 20, 2023

Zaverkin, Viktor; Holzmüller, David; Bonfirraro, Luca; Kästner, Johannes, 2023, "Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials", https://doi.org/10.18419/DARUS-3299, DaRUS, V1

Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach. Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found on GitLab. The data represents TensorFlow v2 checkpoints and stores the metadata for the checkpoint and parameters for the mo...

best_stats_ens.pkl

Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials

Unknown - 331 B -

best_stats_ens.pkl

Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials

Unknown - 331 B -

best_stats_ens.pkl

Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials

Unknown - 216 B -

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