Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [pooling]

17 questions
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1 answer

ValueError: No gradients provided for any variable

I have this error when running training on my model. I found this issue on different sites, but could not find a solution to my problem. Here is my model : import keras import tensorflow as tf import tensorflow.keras.layers as L import…
Catalina Chircu
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5 answers

Real purpose of pooling

Recently I had a doubt as to what is the real purpose of pooling layers in neural networks is? The most common answer is To select the most important feature To increase the receptive field of the network I feel that these are not real reasons…
a_parida
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What's the purpose of padding with Maxpooling?

As mentioned in the question, i've noticed that sometimes there are pooling layers with padding. More specifically, I found this Keras tutorial, where there's a net which contains MaxPooling layers with padding. If padding=same in convolutional…
Mattia Surricchio
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1 answer

Absolute-value max pooling in 2D convolutional neural networks

i am fairly new to machine learning, so this may be a silly question. if that is the case, I apologise in advance. i am training a convolutional neural network on oceanographic images, which include both positive and negative anomalies. The…
Fabio
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1 answer

Trying to average node values over local neighborhoods in a graph using a GCN

I'm new to Graph Convolutional Networks (and pytorch in general) so I'm trying to verify that the message passing layer is working as expected before I go on to adding layers to the network. But when I look at the output of the propagation, it…
dn-ra
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1 answer

What to do with Transformer Encoder output?

I'm in the middle of learning about Transformer layers, and I feel like I've got enough of the general idea behind them to be dangerous. I'm designing a neural network and my team would like to include them, but we're unsure how to proceed with the…
Rstan
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What is dropout in convolutional layers and how does that different from max-pooling-dropout?

When dropout is applied to fully connected layers some nodes will be randomly set to 0. It is unclear to me how dropout work with convolutional layers. If dropout is applied before the convolutions, are some nodes of the input set to zero? If that…
user570593
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The idea behind Generalized Max Pooling

I am trying to understand the idea of "Generalized Max Pooling". It seems they try to make the 'pooled' representation similar to the features. If so I feel some rare discriminating features could not be captured by the 'pooled' representation. The…
user570593
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1 answer

How gradients are learned for pooling layers in Convolution Neural Network?

Assuming we could compute a layerwise Hessian of the error function when training a neural network, the error sub-surface of pooling layers will be flat.?? Is that correct? There is no weights to be learnt for pooling layer but for eg. max pool can…
MAC
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How is the output of a maxpool layer window size=1x2 and stride=2 calculated?

I'm looking at the architecture proposed in the following paper: Baoguang Shi et al, An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition. In the proposed architecture of the…
John T. Copeland
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Is it possible to apply pooling across the channel dimension of the input tensor?

I have an input tensor of the shape (32, 256, 256, 256). In this tensor shape, 32 is the batch size. second 256 is the number of channels in the given image of size 256 X 256. I want to do pooling in order to convert the tensor into the shape(32,…
hanugm
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Max Pooling in first Layer of CNN

I am seeing, in all the notebooks that I found, that Max Pooling is never used in the first layer of a CNN. Why this? Is it a convention among data scientist to do not use max pooling in the first layer? Or is it an error to use in the first layer?
CasellaJr
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The effect of removing pooling layers in the model's accuracy

I know that removing pooling layers will lead to an increase in dimensionality and subsequently, make the training to be more time-consuming. But I'm wondering if it worth it to remove pooling layers or not? does it lead to a higher accuracy? Have…
Fatemeh Asgarinejad
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Exaplain how to visualize 'SAME' Padding with input size 11x11x64 with pool size 2x2 and stride 1?

I have an ML model where I get the convolution output as 11x11x64. Now I have to perform maxpool with pool size (2x2) and stride=1 with padding 'same'. I know the output size will also be 11x11x64. But what I don't understand is how the zeros…
Utkarsh Kathuria
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State of the art in transformer regressors/attention layer aggregation

I am curious to know what the state of the art is in using transformers for regression. Ultimately what I am interested in is how researchers in this field aggregate the outputs of the final attention layer. Has there been anything implemented that…
Zador Pataki
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