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GPU Implementation #53

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GPU Implementation #53

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feb43d6
GPU version
Jeanselme Sep 8, 2021
04125d9
Update all models for GPU
Jeanselme Sep 8, 2021
f737852
Two modes for CUDA
Jeanselme Sep 8, 2021
f436ee2
Fix loss computation
Jeanselme Sep 8, 2021
31bc7de
Pretrain fix
Jeanselme Sep 8, 2021
1d1ab18
Update GPU for list pdf
Jeanselme Sep 8, 2021
6eabc56
Push t to gpu
Jeanselme Sep 8, 2021
9edb9cf
Fix pretraining
Jeanselme Sep 8, 2021
d2a3918
Merge for new contrib
Jeanselme Nov 2, 2021
bcdd2f1
Typo fix
Jeanselme Nov 2, 2021
ad3493b
Add nll computation
Jeanselme Nov 3, 2021
064dc66
Update datasets loading to ensure columns and allow competing risks
Jeanselme Nov 4, 2021
c047098
Framingham evaluate at baseline
Jeanselme Nov 12, 2021
5611a16
Update FRAMINGHAM competing risks
Jeanselme Dec 15, 2021
877b2fa
Add function for cluster assignement
Jeanselme Dec 21, 2021
6d8cefb
Competing risks for PBC
Jeanselme Jan 25, 2022
9fb5d30
Fix outcome
Jeanselme Jan 25, 2022
02d9f50
Focus on baseline evaluation
Jeanselme Feb 17, 2022
3a243a2
Ensure labels 1 same across experiments
Jeanselme Jul 5, 2022
8fd04a8
Update PBC
Jeanselme Jul 5, 2022
e4b07b3
Remove automatic normalization
Jeanselme Jul 20, 2022
cedfaf6
Update temporal normalization
Jeanselme Sep 19, 2022
b29ab6d
Add cluster assignment
Jeanselme Apr 4, 2024
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Update PBC
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@Jeanselme
Jeanselme committed Jul 5, 2022
commit 8fd04a88681ddb5aa549f9bc8278fc19b6013f95
2 changes: 1 addition & 1 deletion dsm/datasets.py
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Expand Up @@ -157,7 +157,7 @@ def _load_pbc_dataset(sequential, competing = False):
x = np.hstack([x1.values, x2.values, x3.values.reshape(-1, 1)])

time = (data['years'] - data['year']).values
event = (data['status'] == 'dead').values
event = (data['status'] == 'dead').values.astype(int)
if competing:
event[data['status'] == 'transplanted'] = 2

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