robintibor
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robintibor
/ BraindecodeSummerSchoolPerturbation.ipynb
Created
January 23, 2021 00:20
Braindecode Tutorial with Perturbation Visualization
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robintibor
/ High_Gamma_Deep4.ipynb
Created
January 14, 2021 12:02
High_Gamma_Deep4 - no trial exclusion
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robintibor
/ margincaptionproblem.ipynb
Created
November 12, 2020 21:22
Jupyter Book will make margin caption below figure :(
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robintibor
/ AttentionExp.ipynb
Created
July 10, 2020 08:31
Decoding Attention Level with Braindecode smaller Windows
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robintibor
/ AttentionExp.ipynb
Last active
July 10, 2020 08:27
Decoding Attention Level with Braindecode
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| epoch train_loss train_trial_accuracy valid_loss valid_trial_accuracy dur | |
| ------- ------------ ---------------------- ------------ ---------------------- ------- | |
| 1 1.3710 0.2565 7.1190 0.2241 12.1600 | |
| 2 1.1152 0.3130 2.7722 0.2069 11.9932 | |
| 3 0.9749 0.6739 1.2467 0.4138 12.0441 | |
| 4 0.8932 0.8261 0.9292 0.6034 12.0141 | |
| 5 0.8167 0.8391 0.8623 0.7586 12.0072 | |
| 6 0.7648 0.8870 0.7970 0.7586 11.9814 | |
| 7 0.6920 0.8609 0.8171 0.7586 11.9903 | |
| 8 0.6505 0.8696 0.8143 0.7241 11.9883 |
robintibor
/ SelectNumbers.ipynb
Created
November 20, 2019 00:08
Select Numbers with all Attributes Vadim
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robintibor
/ Rescale.ipynb
Last active
July 16, 2019 02:47
Rescaling Alphas for Proxyless Gradient-based Update
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| def rescale(a, a_new, i_op_0, i_op_1): | |
| i_op_0 = int(i_op_0) | |
| i_op_1 = int(i_op_1) | |
| old_p = F.softmax(a, dim=0) | |
| new_p = F.softmax(a_new, dim=0) | |
| old_sum = old_p[i_op_0] + old_p[i_op_1] | |
| new_sum = new_p[i_op_0] + new_p[i_op_1] | |
| ratio = old_sum / new_sum | |
| # rescaled probabilties such that sum is same as before | |
| p_r_0 = ratio * new_p[i_op_0] |