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Hey all, as you see from the tensorboard below, the val_loss_rpn_cls and val_loss_class_cls doesnt converge. Im using just a text class and tried different learning rates, VGG16, resnet50 and ROIs.
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when i am printing the imported summaries from the pickled file, its alright. It's fully printed in its encoded form. Vec_texts also prints fine. But vec_summaries_reduced and vec_texts_reduced return…
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When running my code I get the following error `blob.cpp:29] Check failed: shape[i]
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I am trying to create a custom activation layer base on Neupy, however, once I apply my custom layer to the network, the training and validation error keep the same in each epoch. For my custom functi…
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I was just thinking about this on a walk. See section 3.4.6 of the linked document
https://developer.nvidia.com/sites/default/files/akamai/cuda/files/Misc/mygpu.pdf
Therefore our current bottleneck …
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I want to implement [Bayes by Backpropagation (BbB)](https://arxiv.org/abs/1505.05424) in MxNet, but two notable features of this algorithm cause me some confusion.
For one, when I look at [example…
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Hi all,
I defined a constant layer in PaddlePaddle by myself and use FeatureMapExpandLayer on top of that for some learning algorithms. The constant layer I defined does not need backpropagation.
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Last night, I read [1] discussing the combination of PSO and RNNs. In their discussion, the authors found a tradeoff between PSO and back propagation. PSO is good for finding a global maxima/minima …
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Hi @wagenaartje,
I'm wondering, do you have any tests comparing your algorithm with NEAT? I was thinking about implementing my own version of NEAT, but recently I found your lib. It seems to work …
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``````
/```
/ assume, that all neurons of the network have the same activation function
IActivationFunction function = (network.Layers[0].Neurons[0] as ActivationNeuron).ActivationFunction…