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Tim Herfurth proslijedio/la je Tweet
What GPT-2 accidentally reveals about nature, nurture, and the challenge of building intelligence. Prelude to a longer piece on how to best advance AI over the next decade
https://thegradient.pub/gpt2-and-the-nature-of-intelligence/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Tim Herfurth proslijedio/la je Tweet
Our new paper, Deep Learning for Symbolic Mathematics, is now on arXiv https://arxiv.org/abs/1912.01412 We added *a lot* of new results compared to the original submission. With
@f_charton (1/7)pic.twitter.com/GrhQRT5WRW
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Tim Herfurth proslijedio/la je Tweet
What are Transformer Networks, and why are they getting so much hype? New blog post from Ben Cowley unpacking it for you: https://pillowlab.wordpress.com/2019/11/22/attention-is-all-you-need-aka-the-transformer-network/ …pic.twitter.com/LOlhQHGsQ6
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Tim Herfurth proslijedio/la je Tweet
Our opinion piece that deep learning should guide neuroscience research just came out:https://www.nature.com/articles/s41593-019-0520-2 …
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Dear
@seanmcarroll, in several mindscape episodes you state something like "life converts high-entropy energy from the sun into low-entropy energy". I get the basic idea but from all I know entropy is not a property of energy (or photons). Could help me there?Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Tim Herfurth proslijedio/la je Tweet
In new work with
@KordingLab, we reconstruct the architecture, weights, and biases of unknown deep ReLU networks by observing their output. ReLU nets are piecewise linear functions - a lot of info is in the boundaries between linear regions. Full paper: https://arxiv.org/abs/1910.00744 pic.twitter.com/QlhucOcb58
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Tim Herfurth proslijedio/la je Tweet
We are making good progress on
#PyMC4, just yesterday I sampled the 8 schools model with NUTS (all in TF, fully compiled and vectorized across chains). Mostly work by@ferrine96. Very hard to say when and if it will supersede#PyMC3, but we will continue to maintain it either wayhttps://twitter.com/dan_s_becker/status/1169226031124770817 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Tim Herfurth proslijedio/la je Tweet
After 2.5 years, we finally shipped the book off for printing. The GitHub graphs do look a bit scary...
@ChengSoonOng@AnalogAldo You can download the PDF (and some jupyter notebooks) from here: https://mml-book.com pic.twitter.com/qfAd0pgyKj
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thanks! I think I am mostly interested in DAG-focused tools but I'll try to check all of them. Is R a big thing for those working in causal inference?
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is anyone aware of good (and maintained) python tools for causal inference?
#causalinference#bookofwhy@yudapearl@KordingLab@mioanaPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Tim Herfurth proslijedio/la je Tweet
A decoder, which can transform brain activity into speech, is presented in a study published in Nature. The brain–computer interface device synthesizes speech using the neural signals that control lip, tongue, larynx and jaw movements. Read the paper: https://go.nature.com/2vn9RpC pic.twitter.com/ESImSLv0xn
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Tim Herfurth proslijedio/la je Tweet
Fun conversation with Sean Carroll on his podcast. More details in a new preprint we have out https://www.biorxiv.org/content/10.1101/585760v1 …, and a COSYNE talk at https://youtu.be/Q3H-5Z3-6gM .https://twitter.com/seanmcarroll/status/1110183986305757185 …
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excellent intro to causal inference by
@akellehhttps://link.medium.com/GK3X2d67GVHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Tim Herfurth proslijedio/la je Tweet
1/6 Deep classifiers seem to be extremely invariant to *task-relevant* changes. We can change the content of any ImageNet image, without changing model predictions over the 1000 classes at all. Blog post @ https://medium.com/@j.jacobsen/deep-classifiers-ignore-almost-everything-they-see-and-how-we-may-be-able-to-fix-it-a6888012516f …. with
@JensBehrmann Rich Zemel@MatthiasBethgePrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Opening the black box of deep neural networks via information - part I https://blog.acolyer.org/2017/11/15/opening-the-black-box-of-deep-neural-networks-via-information-part-i/ … via
@wordpressdotcomHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Double standards: 'Why aren't we all with Somalia?'
@AJENews http://aje.io/uj6kuHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Tim Herfurth proslijedio/la je Tweet
Nice review paper by Tim Herfurth and Tatjana Tchumatchenko
@MpiBrain in Current Opinion in Neurobiology#linearity https://brain.mpg.de/news-events/news/news/archive/2017/october/article/applications-and-limitations-of-linear-response-functions-in-models-of-neural-circuits.html?tx_ttnews%5Bday%5D=09&cHash=7b4bdf846c89bea92e7e8d7d5593f83f …pic.twitter.com/36V7DDW9Ta
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is there a print version? the link on http://ciml.info does not lead me anywhere.https://twitter.com/haldaume3/status/910861549635559424 …
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highly recommend A Course in Machine Learning by
@haldaume3 (see http://ciml.info/ )Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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