Comments (8)
Hi @JosephKJ,
Thanks for your interest in our work.
I will send you the implementation of PODNet + AANets in several days.
Best,
Yaoyao
from class-incremental-learning.
Hi @JosephKJ,
This is the code for POD+AANets: https://drive.google.com/file/d/1ngKvJNWUxTnl-KiQk9pDTJD4scPqKRaV/view?usp=sharing
As I haven't cleaned up the code, it would be a bit messy. I am sorry for that.
If you have any further questions, feel free to email me or add comments to this issue.
Best,
Yaoyao
from class-incremental-learning.
Thank you very much, @yaoyao-liu! I have requested access to the drive folder, kindly allow when you get a chance.
Thanks again!
Joseph
from class-incremental-learning.
Just received. Thank you very much :)
from class-incremental-learning.
Hi,i also need the code. I have requested access to the drive folder,please allow when you are free
from class-incremental-learning.
I have allowed it.
from class-incremental-learning.
Hello, I also request access to the code for my experiments. Please allow me when you are free.
Thanks a lot!
from class-incremental-learning.
Hi @bellos1203,
I have allowed it. If you have further questions, feel free to contact me.
from class-incremental-learning.
Related Issues (20)
- runs the code in mini-imagenet HOT 1
- How are the hyperparameters tuned? HOT 1
- Paper uses dynamic budget, but repository recommends fixed? HOT 2
- Question about exemplar selection code HOT 2
- Running errors HOT 3
- ValueError: signal number 32 out of range HOT 1
- This is a very strange question HOT 1
- some bugs HOT 3
- Code for T-SNE in the mnemonics paper HOT 4
- `BaseTrainer.init_current_phase_dataset` returning two `Y_valid_cumuls` HOT 2
- question about `modified_linear.py` HOT 2
- size of trainloader HOT 4
- training problem HOT 9
- Inquiries about the comparison between mnemonics and baseline HOT 2
- Kindly explain a little about the results terms and accuracy matching HOT 8
- PODNET-AAN Related experiment running issue! HOT 4
- Save model in PODNET repo HOT 1
- About initializing learnable parame φi and ηi HOT 4
- training hyperparamters for imagenet1000? HOT 2
- Implementations of Mnemonics training HOT 4
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