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Hello, thank you for your amazing work. Could you share the code for training psMNIST with pre-processing? In SNN work, pre-processing should play an important role in good performance. Thank you.
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Dear authors,
Congratulations on your acceptance to ICML 2024! I am the first author of SpikeBERT, and I am very grateful for your citation of our work. I am also delighted to see the integration o…
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At the same time, I would like to kindly inquire about the training details, such as the dataset, pre-training, optimizer, and training time. Additionally, I am interested in the reasons behind the su…
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Please:
- [x] Check for duplicate requests.
- [x] Describe your goal, and if possible provide a code snippet with a motivating example.
Implementation of the online learning algorithms for spik…
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In `spiking_vgg.py` average pooling is used in favor of max pooling for the VGG's pooling layers. What is the reason for this deviation?
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I try your code in two ways in COCO2014 dataset,
1)in ultralytics/yolov3 branche , use cfg/yolov3-tiny-ours.cfg, i can reach 38.70% map, but I use "python3 ann_to_snn.py xx", yolov3-tiny-our…
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**Issue type**
- [ ] Bug Report
- [ ] Feature Request
- [X] Help wanted
- [] Other
**Description**
Hi @fangwei123456. First of all, congratulate you for the great work you have done with S…
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Hi there,
I am currently using the brevitas weight_bit_width quantisation for quantisation aware training on a convolutional SNN.
Since this method outperforms my other QAT methods, I am wondering…
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Hello.
I trained ann model for CIFAR10 by using ann.py.
After that, I run snn.py to train SNN by STDB.
Converting CNN to SNN works fine.
However, accuracy continues to decrease as epoch con…
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I am trying out this code (https://github.com/fangwei123456/spikingjelly/blob/master/spikingjelly/activation_based/ann2snn/examples/cnn_mnist.py). The only difference is I have changed the CNN archite…