Comments (2)
snowkylin
commented on July 28, 2024
I do not find specific instruction in the paper that some part of the gradients should be stopped. Maybe you can try your method and see how the result will be?
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david-wb
commented on July 28, 2024
I tried it and the model fails to learn in a reasonable time. This makes me think original NTM was fundamentally an RNN, even the one with the feed forward controller which must have used recurrence on the memory, weights, and reads. Anyway, thanks for responding.
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Related Issues (20)
- Can You please upload the link to the data set(MANN) ? HOT 1
- Can you please explain about the accuracy mechanism in the model ? HOT 1
- Converging of the network for different data sets? HOT 6
- copy_task.py stopped with NotFoundError HOT 3
- small correction about argument parsing in copy_task.py HOT 1
- No model_checkpoint_path error when copy_task.py --mode test HOT 1
- data folder for one_shot_learning.py ?
- num_parameters_per_head confused? HOT 3
- How to use model for Inference HOT 7
- What is key vector? HOT 2
- Memory tends to be the same? And the confusion about MANN
- Using MANN in A3C (reinforcement learning model) HOT 3
- instance
- Training the Model HOT 1
- Initialization regarding the addressing and memory matrix . HOT 4
- can you explain about the plotting read vectors ? HOT 3
- How did you calculate the number of controller output parameters in MANN cell ? HOT 2
- confusion when calculating the least used weight vector in MANN HOT 6
- Why we need to set the least used memory location to zero in the memory matrix HOT 2
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