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Prikvačeni tweet
Today we introduce two large spike-based data sets for the quantitative comparison of spiking neural network architectures and neuromorphic hardware. Creative Commons License. Data: https://compneuro.net Paper: https://arxiv.org/abs/1910.07407 pic.twitter.com/5dXFnMJwNR
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Friedemann Zenke proslijedio/la je Tweet
Today I will be teaching my undergrad course "How to build a brain from scratch" for the 2nd year running. I've put the materials online - include a document with all lecture slides and notes, which is about as long as a decent novel. Enjoy!https://humaninformationprocessing.com/teaching/
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Friedemann Zenke proslijedio/la je Tweet
I'm thrilled to be starting my research group in
@OxExpPsy at@UniofOxford. Interested in deep learning theory and neuroscience? I'm looking for team members! http://www.saxelab.orgHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Friedemann Zenke proslijedio/la je Tweet
How does transfer learning for medical imaging affect performance, representations and convergence? Check out the blogpost below and our
#NeurIPS2019 paper https://arxiv.org/abs/1902.07208 for some of the surprising conclusions, new approaches and open questions!https://twitter.com/GoogleAI/status/1203026419883732992 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Our Surrogate Gradient Learning tutorial paper now appeared in IEEE SPM https://ieeexplore.ieee.org/document/8891809 …. For those who are paywalled (ironically this includes me) here is the preprint https://arxiv.org/abs/1901.09948 pic.twitter.com/dfhGH5ixKx
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Friedemann Zenke proslijedio/la je Tweet
1/ SciTwitter: I'm very excited to share our new Perspective article out in Nature Neuroscience today!https://www.nature.com/articles/s41593-019-0520-2 …
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Friedemann Zenke proslijedio/la je Tweet
Happy to present the latest co-production of the Ferraguti
@imed_tweets & Lüthi@FMI labs with@l_e_r_r_y - VIP interneurons indeed are "very important players" for learning!https://www.nature.com/articles/s41593-019-0508-y …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Friedemann Zenke proslijedio/la je Tweet
Single-trial variability in spike timing, even in small amounts, can mask striking firing patterns. The raster plots below show the same data (a neuron from rat motor cortex). The only difference is that we’ve re-sorted the trial ids with the help of a simple model.pic.twitter.com/mnskISaETS
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Coming up: EPFL Neurosymposium “Neuroscience meets Deep Learning” July 8th to July 9th 2019 in Lausanne, Switzerland https://neurosymposiumsummer2019.epfl.ch/
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Friedemann Zenke proslijedio/la je Tweet
Exciting work in the evolution approach and meta learning! —
@Luke_Metz blowing us away with neuron local meta learned update rules and their surprising generalization ability (across datasets, data modalities, and architecture!!)@jaschasd https://arxiv.org/abs/1804.00222 pic.twitter.com/a7wfOWKPOS
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Two days left to apply for PhD positions at the http://zenkelab.org and at the FMIhttps://www.fmi.ch/PhD/
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Friedemann Zenke proslijedio/la je Tweet
Interested in the latest developments in theoretical neuroscience? Want to learn and discuss how tools from math and physics are applied to neural networks? Want to visit the historic workplace of Gauss, Webber, Planck, Hilbert, Minkowski? Register now! http://www.neuro-theory.org pic.twitter.com/Dw2FBqPKRx
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Want to play with spiking neural networks trained with surrogate gradients? Here is a simple tutorial in PyTorch which should give you everything you need to get startedhttps://github.com/fzenke/spytorch
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Friedemann Zenke proslijedio/la je Tweet
The http://vogelslab.org (me) is looking to fill several postdoc positions in the near future. If you are good at neuro-math-coding & interested in neuronal network dynamics, memory, plasticity & machine learning, drop me a line, or chat me up at
#cosyne19 RT please.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Short review/tutorial on different approaches for training spiking neural networks using surrogate gradients https://arxiv.org/abs/1901.09948 with
@virtualmind and Hesham. Includes a section that elucidates the connection of SuperSpike and RTRL. Feedback welcome.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
I should correct myself: It is rather a supervised similarity matching loss.
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Very encouraging results from extending the notion of layer-wise "local error signals" (https://arxiv.org/abs/1711.06756 ) with an unsupervised similarity matching loss.https://twitter.com/arild567/status/1087964691450789894 …
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Friedemann Zenke proslijedio/la je Tweet
#COSYNE19 Workshop: Why Spike? Understanding the power and constraints of spiking based computation in biological and artificial neuronal networks https://whyspike.wordpress.com featuring@NeuroNaud,@compneuro_epfl,@hisspikeness and more!#neuromorphic#SNNpic.twitter.com/XVD6gpxSAO
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Friedemann Zenke proslijedio/la je Tweet
My new post for the
@Stanford Human Centered AI Initiative: a personal vision of how#neuroscience#psychology#ai#physics#mathematics and other fields can work together to both understand biological intelligence and create artificial intelligence! https://hai.stanford.edu/news/the_intertwined_quest_for_understanding_biological_intelligence_and_creating_artificial_intelligence/ …pic.twitter.com/Uc6T9uu5xx
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Neat work on how the dynamical repertoire of a recurrent network changes by tuning neuronal gains only. Somewhere in-between reservoir computing and training all parameters of an RNN.https://twitter.com/jakepstroud/status/1067361233056210944 …
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