PN 6

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

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571 to 580 of 867 Results

ckpt-137.index Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 2.0 KB - MD5: 6315322f1afe644b1c1e0dccc2dce8ab
ckpt-138.data-00000-of-00001 Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 10.8 MB - MD5: 06c4e27ea094814f4ba4e7a6f5c97e13
ckpt-138.index Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 2.0 KB - MD5: 32c2f6d3ec78fcc742c193dee994dbf6
ckpt-144.data-00000-of-00001 Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 10.8 MB - MD5: 12c83e97acd358343f08d32cb5936292
ckpt-144.index Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 2.0 KB - MD5: 5b0bc8ab52a26c6a409ae603e7044f45
ckpt-145.data-00000-of-00001 Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 10.8 MB - MD5: 9b21aa7053bec0bdbb55a95484bf7ef5
ckpt-145.index Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 2.0 KB - MD5: e3f90516fb4a2274760eddb390b46409
ckpt-158.data-00000-of-00001 Feb 20, 2023 - Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Unknown - 10.8 MB - MD5: 48b5a5751180054789b3fa006e13d618
Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v2] Aug 24, 2022 Holzmüller, David; Zaverkin, Viktor; Kästner, Johannes; Steinwart, Ingo, 2022, "Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v2]", https://doi.org/10.18419/DARUS-3110, DaRUS, V1 This dataset contains code and data for the second arXiv version of our paper "A Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Active Learning problems. The code is also available on GitHub. Informat...
algorithms.py Aug 24, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v2] Python Source Code - 26.9 KB - MD5: fbf003864bf024b0fd1fd8750f249ac2

ckpt-137.index

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

Unknown - 2.0 KB -

ckpt-138.data-00000-of-00001

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

Unknown - 10.8 MB -

ckpt-138.index

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

Unknown - 2.0 KB -

ckpt-144.data-00000-of-00001

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

Unknown - 10.8 MB -

ckpt-144.index

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

Unknown - 2.0 KB -

ckpt-145.data-00000-of-00001

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

Unknown - 10.8 MB -

ckpt-145.index

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

Unknown - 2.0 KB -

ckpt-158.data-00000-of-00001

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

Unknown - 10.8 MB -

Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v2]

Aug 24, 2022

Holzmüller, David; Zaverkin, Viktor; Kästner, Johannes; Steinwart, Ingo, 2022, "Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v2]", https://doi.org/10.18419/DARUS-3110, DaRUS, V1

This dataset contains code and data for the second arXiv version of our paper "A Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Active Learning problems. The code is also available on GitHub. Informat...

algorithms.py

Aug 24, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v2]

Python Source Code - 26.9 KB -

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