PN 6-3

SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation"

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41 to 50 of 55 Results

requirements.txt Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Plain Text - 637 B - MD5: 09b283d76024ec31e9134f8d4bf7636d
run_nn_setups.py Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Python Source Code - 30.7 KB - MD5: ea8311dc8c3e079b3caa9a1c6774412a
show_training.py Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Python Source Code - 17.1 KB - MD5: c0aeba6d65554d5395ca28296a781ea0
tex_head.txt Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Plain Text - 4.9 KB - MD5: 4c5247ed7dab1c2c29f8e470d1dc271e
tex_tail.txt Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Plain Text - 124 B - MD5: 47aeb495fcff06691708ae2515da5e49
TrainingSetup.py Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Python Source Code - 11.2 KB - MD5: 73b9c67f5a7a2513bee4c2b93e33e34c
train_star_dataset.py Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent Python Source Code - 20.0 KB - MD5: 92dd31d212970c4a430d131855d5631d
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
computation.py Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Python Source Code - 16.2 KB - MD5: 727ea9050972d03f12c6aa5b32b7e37c
data.tar.gz Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Gzip Archive - 5.6 GB - MD5: 220970917c2371206a808c02bbb9f359 Data Data generated by running the code

requirements.txt

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

Plain Text - 637 B -

run_nn_setups.py

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

Python Source Code - 30.7 KB -

show_training.py

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

Python Source Code - 17.1 KB -

tex_head.txt

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

Plain Text - 4.9 KB -

tex_tail.txt

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

Plain Text - 124 B -

TrainingSetup.py

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

Python Source Code - 11.2 KB -

train_star_dataset.py

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

Python Source Code - 20.0 KB -

utils.py

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

Python Source Code - 2.9 KB -

computation.py

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Python Source Code - 16.2 KB -

data.tar.gz

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Gzip Archive - 5.6 GB -

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