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Viewing profile — eref

eref

HN member
Joined
Sun, Nov 05, 2017, 6:40 PM UTC
HN karma
117
Public activity
56 items

About eref

Off-the-shelf hacker with diverse interests in AI, graphics and armchair philosophy.

Recent public activity

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    Comment #15969321

    I do not get what makes this post so popular. Google Maps is often better and uses automatically extracted features from photogrammetry. Eh. 350 points at most.

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    Comment #15956992

    For me on Firefox on macOS that is just a couple of key strokes away: cmd-l cmd-c ctrl-a r u r l : cmd-t cmd-v ctrl-a h n I have set up `r` as keyword to search on Reddit and `hn` …

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    Comment #15953909

    Why not both?

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    Comment #15940171

    The term "circuit" is used in neuroscience all of the place.

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    Comment #15940087

    Capsules basically do a kind of self-attention. But there the parent features compete for a coupling, not the child features.

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    Comment #15932350

    Same with 57.0 on macOS 10.12. Edit: I have FF Studies disabled under about:preferences#privacy. I guess that is the reason why it is not installed on my machine.

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    Comment #15903351

    The new XPS 13 has a better camera position and a good touch pad but still not a great battery. It’s close. Maybe next year.

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    Comment #15876071

    > simulate a physical environment very fast That's probably only a problem if it is must faster than everbody else. > let alone faster than what happens in our environment That is …

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    Comment #15867076

    The question is whether the overall gains outnumber the local losses.

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    Comment #15860037

    The main problem is that we still lack good generative models and good ways of interrogating them. GANs are unstable and difficult to apply to time series, VAEs suffer from posteri…

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    Comment #15828314

    But what does have to do with smoothness and translation invariance which this paper is a demonstration of? You even learn Gabor filters with local connectivity without spatial wei…

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    Comment #15822386

    What do Gabor filters have to do with this?

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    Comment #15822370

    I think that can be mainly attributed to the fact that the last few deconvolutional features are overfitted to features in the image and are somewhat robust to noise. The network d…