PN 6

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

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621 to 630 of 846 Results

utils.py Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Python Source Code - 2.9 KB - MD5: 44757495ab97921515a4296648fed8a3
algorithms.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 26.1 KB - MD5: 135174e733df1a4b2987aa0cb450c4a3
analysis.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 22.1 KB - MD5: 50ac2de7ed2628a62f3ea8727751e027
benchmark.ipynb Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Jupyter Notebook - 111.5 KB - MD5: 96b0ac084968162443906c31b9a16dbf
check_task_learnability.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 3.3 KB - MD5: 3589368ab168cf46c8a7222f1e2acf29
custom_paths.py.default Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Unknown - 498 B - MD5: 0aa70e1f521326332f33f70b938dc292
data.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 15.4 KB - MD5: 5c2cdd3bdee3b38e4fddb8b7a2d7fec8
data.tar.gz Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Gzip Archive - 1011.3 MB - MD5: 2b34cf7ecdb8fa51046ade430586c22e Compressed folder containing downloaded raw and processed data sets as generated by download_data.py at the time of running the experiments.
download_data.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 26.3 KB - MD5: 0994f8b09885fc142fc3c54edea4af23
feature_data.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 22.6 KB - MD5: 785739ec720d94ff1adeb439c0535deb

utils.py

Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent

Python Source Code - 2.9 KB -

algorithms.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 26.1 KB -

analysis.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 22.1 KB -

benchmark.ipynb

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Jupyter Notebook - 111.5 KB -

check_task_learnability.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 3.3 KB -

custom_paths.py.default

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Unknown - 498 B -

data.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 15.4 KB -

data.tar.gz

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Gzip Archive - 1011.3 MB -

Compressed folder containing downloaded raw and processed data sets as generated by download_data.py at the time of running the experiments.

download_data.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 26.3 KB -

feature_data.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 22.6 KB -

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