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Aren't Capsule Networks one of this hyped ideas - everyone was talking about them (because their rationale sounded interesting, and well, Hinton) were never see
by stared 8y ago
Aren't Capsule Networks one of this hyped ideas - everyone was talking about them (because their rationale sounded interesting, and well, Hinton) were never seen again?
It is very different to good ideas, like 3x3 conv, dropout, batch norm, residual connections - which once introduced, become standard building block of networks.
- MAXPOOL 8y agoThey are not hyped. Capsule nets are in early phase of research. The bleeding edge deep learning research that tries to push the science forward is trying to develop new ideas. Hinton et. al developed the current deep learning revolution gradually over decades. Next non-incremental revolutions in the field may take similar time to mature.
- heyitsguay 8y agoOh for sure! Not everybody needs to be trying to max out the standard benchmarks with every paper. But have there been any new developments or improvements with capsule nets since the original paper? This blog post looks like it only references that first one, which is coming up on two years old, right? It'd be great to read about any followup.
- stochastic_monk 8y agoGraph Capsule Convolutional Networks [0] claim to have beaten the state of the art in graph neural networks. However, I can’t find information on training time, which I think is significantly more expensive for capsule networks. [0] https://arxiv.org/abs/1805.08090 https://arxiv.org/abs/1805.08090
- sjg007 8y agoThere are 4 problems that need to be solved: translation, rotation, reflection and dilation. Capsule networks are potentially one way to do that.