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  • What is the difference between Conv1D and Conv2D?
    I will be using a Pytorch perspective, however, the logic remains the same When using Conv1d (), we have to keep in mind that we are most likely going to work with 2-dimensional inputs such as one-hot-encode DNA sequences or black and white pictures The only difference between the more conventional Conv2d () and Conv1d () is that latter uses a 1-dimensional kernel as shown in the picture
  • What does 1x1 convolution mean in a neural network?
    1x1 conv creates channel-wise dependencies with a negligible cost This is especially exploited in depthwise-separable convolutions Nobody said anything about this but I'm writing this as a comment since I don't have enough reputation here
  • Convolutional Layers: To pad or not to pad? - Cross Validated
    If the CONV layers were to not zero-pad the inputs and only perform valid convolutions, then the size of the volumes would reduce by a small amount after each CONV, and the information at the borders would be “washed away” too quickly " -
  • How is RELU used on convolutional layer - Cross Validated
    The answer that you might be looking for is that ReLU is applied element-wise (to each element individually) to the learned parameters of the conv layer ("feature maps")
  • Pooling vs. stride for downsampling - Cross Validated
    Pooling and stride both can be used to downsample the image Let's say we have an image of 4x4, like below and a filter of 2x2 Then how do we decide whether to use (2x2 pooling) vs (stride of 2)?
  • neural networks - Difference between strided and non-strided . . .
    conv = conv_2d (strides=) I want to know in what sense a non-strided convolution differs from a strided convolution I know how convolutions with strides work but I am not familiar with the non-str
  • How do bottleneck architectures work in neural networks?
    We define a bottleneck architecture as the type found in the ResNet paper where [two 3x3 conv layers] are replaced by [one 1x1 conv, one 3x3 conv, and another 1x1 conv layer] I understand that t
  • What is MBConv that EfficientNetv2 is using? - Cross Validated
    EfficinetNetV2 uses MBConv Fused-MBConv as a part of it's architecture There is no clarity of what these operations actually are from the paper (nor from the references) It appears that it is som





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