Tweetovi
- Tweetovi, trenutna stranica.
- Tweetovi i odgovori
Blokirali ste korisnika/cu @Ganeshk92
Jeste li sigurni da želite vidjeti te tweetove? Time nećete deblokirati korisnika/cu @Ganeshk92
-
M Ganeshkumar proslijedio/la je Tweet
Beautiful, simple and elegant. Lateral PFC reflects and predicts conscious content in the absence of motor reports. Also, a clear example of why we should be careful about the interpretation of fMRI results (as well as why we need more single neuron work)https://twitter.com/biorxiv_neursci/status/1222298808090091520 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
#TransferLearning is one of the most important#AI techniques I don't often recommend PhD Thesis' -@seb_ruder's is exceptional. He's a brilliant writer! Check out this taxonomy / table of contents!!!

#100DaysOfMLCode#100DaysOfCode https://ruder.io/thesis/neural_transfer_learning_for_nlp.pdf …pic.twitter.com/ZSbZSwD9DT
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
As far as current machine learning is concerned, generalization originates from the ability to learn the latent manifold on which the training data lies, i.e. the ability to interpolate between training samples (local generalization, by definition)
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Update on the 2013 paper on memory schema and the complementary learning system by McClellandhttps://www.biorxiv.org/content/10.1101/2020.01.17.909804v1 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Q-learning is difficult to apply when the number of available actions is large. We show that a simple extension based on amortized stochastic search allows Q-learning to scale to high-dimensional discrete, continuous or hybrid action spaces: https://arxiv.org/abs/2001.08116
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
New results: Achieving stable dynamics in neural circuitshttps://www.biorxiv.org/content/10.1101/2020.01.17.910174v1 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Read our
@nature paper "A distributional code for value in dopamine-based reinforcement learning" online here: https://rdcu.be/b0mtAHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
When neuroscience and AI researchers get to chatting, cool stuff happens! My first, and I hope not last, trip into neuroscience has been published in Nature. 1/https://twitter.com/DeepMind/status/1217510884085583873 …
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
We have 2 papers published in
@nature today!
One describes AlphaFold, which uses deep neural networks to predict protein structures with high accuracy. AlphaFold made the most accurate predictions at the 2018 scientific community assessment CASP13. 1/4https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Are you confused about all these results in the fMRI literature on motor learning? Increases, decreases, shifts of activity, pattern change, changes in connectivity? We were as well… (1/n)https://twitter.com/biorxivpreprint/status/1215360675612110851 …
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Latent dynamics in the neural
#manifold across three cortical areas in monkeys are stable throughout years of consistent behavior https://go.nature.com/35sIGt9 pic.twitter.com/mBlNUsAQFU
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
If you are a young PI in a learning/compneuro related area, I recommend checking out the
@CIFAR_News Scholars program (https://www.cifar.ca/next-gen/global-scholars …). They have multiple open slots. And it is an understatement that they have many good people (https://www.cifar.ca/research/program/learning-in-machines-brains …)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
*REMINDER + PLS RT* Our workshop, From Neuroscience to Artificially Intelligent Systems (NAISys), has an abstract deadline of January 10. This Friday!!! But, it's only 1-page, so easy-peasy: https://meetings.cshl.edu/meetings.aspx?meet=NAISYS&year=20 … Please send in ideas for how neuroscience can inform AI!pic.twitter.com/AZNNIUSg0N
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Despite Deep
#ReinforcementLearning's popularity, there are precious few good intro tutorials! This is a really nice one. It combines: - toy implementation - math concepts - intuitive explanations#100DaysOfMLCode#100DaysOfCodehttps://medium.com/@dhruvp/how-to-write-a-neural-network-to-play-pong-from-scratch-956b57d4f6e0 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Excited to share a new review on all things Engram Susumu Tonegawa (
@MIT_Picower) and I wrote Memory engrams: Recalling the past and imagining the future https://science.sciencemag.org/content/367/6473/eaaw4325 … 1/3Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Just got sent the printed preview version of "Dive into deep learning" for which there is the free interactive online version: http://d2l.ai/ - omg this text book is so awesome.
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Neurons in primate
#hippocampus non-linearly mix information about space and non-spatial elements of the environment in a task-dependent manner; this efficient code flexibly represents unique perceptual experiences and corresponding memories https://go.nature.com/2ZisOrF pic.twitter.com/TKicGRlCYE
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Starting Jan 6, we're doing a series of lectures at MIT on deep learning and AI. Skip the first one, but afterwards there are some great talks (inc.
@fchollet,@iamtrask). All are welcome. Seating limited (1st come, 1st served). Video will be posted here: https://deeplearning.mit.edu/ pic.twitter.com/xEZ5JFDTnC
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Visualizing MNIST classification. Neat. https://github.com/okdalto/VisualizeMNIST …pic.twitter.com/gUArKRi2J2
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
M Ganeshkumar proslijedio/la je Tweet
Attention is one of the most important breakthroughs in the history of Deep Learning. This
@distillpub is definitively the best explanation of it I've seen. For#100DaysOfMLCode /#100DaysOfCode folks - try building an attention mechanism from scratch! https://distill.pub/2016/augmented-rnns/ …pic.twitter.com/vzXBcQmjfG
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.