Can someone please explain in simple terms and examples on how these work after performing the conv2d forward pass.
Let me add to this question - What is the difference between conv2d_backprop_filter and tf.nn.conv2d_backprop_input?
For an explanation of conv2d_transpose I would look at other stack overflow questions such as this one: conv2d_transpose
As for conv2d_backprop_filter: this is what is computed during backpropagation to be passed to the previous layer. It has been used for things such as Deep Dream and creation of adversarial examples.