Comments (2)
Hi there,
Thanks for your interest in our work! I actually feel like this correlation looks pretty good already (if you are referring to the correlation between reconstructed fMRI and original fMRI). Also, the correlation may or may not reflect the performance of your downstream task.
You may try on the image reconstruction task and see how it goes! :)
Good luck!
from mind-vis.
Thank you for your response! I appreciate your feedback on the correlation between the reconstructed fMRI and the original fMRI. I am glad to hear that you think the correlation looks good.
I understand that the correlation may not necessarily reflect the performance of my downstream task, but I will certainly take your suggestion and try it out on the our tasks. I will keep you updated on my progress.
from mind-vis.
Related Issues (20)
- Weights and biases for SC-MBM HOT 1
- Bugs when running 'StageB_ldm_finetune.py' HOT 7
- Encountered problem while running Stage B HOT 1
- Understanding the code and architecture HOT 1
- Question about experimental result HOT 1
- Visualize the stimuli
- Pre-trained model HOT 1
- Where to get the Human Connectome Projects (HCP) is right? HOT 1
- How to get the HCP_visual_voxel.npz file?
- Save half training?
- How can I get the "HCP_visual_voxel.npz" for pre-training? HOT 3
- The link is inaccessible
- Use of Test Set for Fine-Tuning
- One question for the Sparse-Coded
- A Question about Low Correlations in the "stageA2_mbm_finetune" Execution on the GOD Dataset HOT 5
- A question about the parameter settings in the stageA2mbm_finetune.py
- Elaboration on Sampler code
- Does the amount of training data in MBM_pretrain_stage matter a lot?
- Does the amount of training data in MBM_pretrain_stage matter a lot? HOT 4
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from mind-vis.