fabianp
/ polynomial_schedule.ipynb
Created
August 30, 2024 12:00
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fabianp
/ linear_schedule.ipynb
Created
August 29, 2024 07:50
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fabianp
/ constant_schedule.ipynb
Created
August 28, 2024 14:08
animation of the constant schedule in optax
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fabianp
/ jaxopt.ipynb
Last active
May 31, 2022 20:37
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fabianp
/ flax_resnet_pytorch.py
Created
February 14, 2022 16:23
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| # Copyright 2021 Google LLC | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # https://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, |
fabianp
/ flax_resnet_groupnorm.py
Last active
February 1, 2022 20:33
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| # Copyright 2021 Google LLC | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # https://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, |
fabianp
/ backtrack.ipynb
Created
June 20, 2018 23:25
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fabianp
/ SAGA-dask.ipynb
Last active
June 5, 2018 19:44
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fabianp
/ frank_wolfe.py
Created
March 19, 2018 18:40
Python implementation of the Frank-Wolfe algorithm
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| import numpy as np | |
| from scipy import sparse | |
| # .. for plotting .. | |
| import pylab as plt | |
| # .. to generate a synthetic dataset .. | |
| from sklearn import datasets | |
| n_samples, n_features = 1000, 10000 | |
| A, b = datasets.make_regression(n_samples, n_features) |
fabianp
/ basic_saga.ipynb
Created
November 8, 2017 19:03
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