Tweetovi
- Tweetovi, trenutna stranica.
- Tweetovi i odgovori
- Medijski sadržaj
Blokirali ste korisnika/cu @MattGolub_Neuro
Jeste li sigurni da želite vidjeti te tweetove? Time nećete deblokirati korisnika/cu @MattGolub_Neuro
-
Matt Golub proslijedio/la je Tweet
Super excited to see this work published! Congrats to Emily for finishing such an awesome project. These were super difficult experiments for her to run, and a really challenging problem to think through!
@MattGolub_Neuro@AlanDegenharthttps://www.pnas.org/content/early/2019/06/06/1820296116 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Golub proslijedio/la je Tweet
New work out on arXiv! Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics (https://arxiv.org/abs/1906.10720 ), with fantastic co-authors
@ItsNeuronal,@MattGolub_Neuro,@SuryaGanguli and@SussilloDavid.#tweetprint summary below!
(1/4)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We hope this tool inspires you to unleash modern deep learning approaches toward understanding how networks and brains solve challenging tasks!
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
FixedPointFinder identifies the stable (black) and unstable (red) fixed points, along with linearized dynamics local to each fixed point (red lines are dominant modes). Trajectories of the network state are overlaid in blue.pic.twitter.com/P4vXoqI8Nt
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Here’s an example--we trained a 16-unit LSTM network to implement a 3-bit memory (a.k.a. the Flip Flop task). Each input (gray) delivers transient pulses to flip the state of a corresponding output (trained network: purple; training signal: cyan).pic.twitter.com/iivDDtks0o
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We've created a Tensorflow toolbox for reverse engineering trained RNNs (with
@SussilloDavid). You train a network (e.g., "vanilla", LSTM, GRU, custom), then we use TF to do the fixed point optimizations and Jacobian computations. http://joss.theoj.org/papers/10.21105/joss.01003 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Golub proslijedio/la je Tweet
Great work, Megan, Christeva, and colleagues! It’s reassuring to see that every once in a while, the answer is not “Motor cortex just does everything”.https://twitter.com/biorxiv_neursci/status/1038974381786062850 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We've posted code to accompany our 2015 eLife paper. The framework extracts a subject's internal model of a dynamical system being controlled. Perhaps useful for those studying BMI / motor / control / learning! https://elifesciences.org/articles/10015 https://github.com/mattgolub/internal_model_estimation …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Golub proslijedio/la je Tweet
Deep convolutional neural networks are great models of the visual system, but these static systems don't explain the temporal dynamics of real visual responses. So we built deep recurrent networks:
@aran_nayebi@qbilius@SussilloDavid@NeuroAILab Paper: https://arxiv.org/abs/1807.00053 pic.twitter.com/veyXeg5RGi
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
To reach or not to reach, that was the question. New work from
@JonAMichaels et al shows that preparatory activity in F5 and AIP separates according to anticipated delays.https://twitter.com/JonAMichaels/status/1009505678149316608 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Golub proslijedio/la je Tweet
Most of you know me as a successful neuroscientist / deep learning researcher but I have a story that I want to share briefly. I grew up in a group home, which is basically an orphanage.https://twitter.com/MaddowBlog/status/1007806343053496320 …
1:02Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
How does the brain quickly learn to improve behavior, and what are the limitations this type of learning? Check out our latest paper, "Learning by neural reassociation," as featured in Byron Yu's
#cosyne2018 talk.https://www.nature.com/articles/s41593-018-0095-3 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matt Golub proslijedio/la je Tweet
First tweet, new paper: we asked can learning motor tasks in your mind w/o physical movements (via a BMI) ‘transfer’ and improve overt behavior, & if so, by what neural mechanism? Thx co-authors
@NirEvenChen@sergeydoestweet@shenoystanford Paul & Stephen http://www.cell.com/neuron/fulltext/S0896-6273(18)30065-5 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
Čini se da učitavanje traje već neko vrijeme.
Twitter je možda preopterećen ili ima kratkotrajnih poteškoća u radu. Pokušajte ponovno ili potražite dodatne informacije u odjeljku Status Twittera.