SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation"
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utils.py
Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression
Python Source Code - 2.6 KB - MD5: f921b3cd6389ea9f8e4707a3655a75f7
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
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
tex_tail.txt
Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
Plain Text - 124 B - MD5: 47aeb495fcff06691708ae2515da5e49
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
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
sampling.py
Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression
Python Source Code - 11.1 KB - MD5: 1a719b0984045eca7ce97bc54b4b9e2b
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
requirements.txt
Jun 20, 2022 - Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
Plain Text - 637 B - MD5: 09b283d76024ec31e9134f8d4bf7636d
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