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Yevgeniy Ivanchenko proslijedio/la je Tweet
New NLP News: NLP Progress, Restrospectives and look ahead, New NLP courses, Independent research initiatives, Interviews, Lots of resources (via
@revue)http://newsletter.ruder.io/archive/217744Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Understanding Deep Learning through Neuron Deletion https://goo.gl/TKesX5
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Check out AmoebaNets, state-of-the-art programmatically evolved
#NeuralNetworks from the Google Brain team (http://g.co/brain ), and one of the latest results from our broader#AutoML efforts → http://goo.gl/Ynj7V3 pic.twitter.com/PmZyCfCC9n
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Yevgeniy Ivanchenko proslijedio/la je Tweet
How do
#NeuralNetworks do what they do? Today,@distillpub published a new article exploring how networks make decisions. Also released is Lucid, a neural network visualization library, along with colab notebooks to produce your own visualizations → http://goo.gl/HYyYa2 pic.twitter.com/lbKLwyp8FfHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Yevgeniy Ivanchenko proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Yevgeniy Ivanchenko proslijedio/la je Tweet
#PyTorch implementation of@DeepMindAI's Visual Interaction Networks https://github.com/Mrgemy95/visual-interaction-networks-pytorch … Blog: https://deepmind.com/blog/neural-approach-relational-reasoning/ …pic.twitter.com/5nyEzkHOtD
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Our new paper in the Journal of Artificial Intelligence Research (JAIR) demonstrates how deep neural networks can be extended to generalise visually and symbolically. https://deepmind.com/blog/learning-explanatory-rules-noisy-data/ …pic.twitter.com/7eDtFHhVQs
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Our latest paper in
@SciReports describes a surprisingly simple way to understand asymmetric games, with possible implications for economics, empirical game theory and environments where multiple AI systems operate https://deepmind.com/blog/game-theory-insights-asymmetric-multi-agent-games/ …pic.twitter.com/z0h6Te5YBO
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Releasing gradient checkpointing - a package for fitting bigger Tensorflow models onto your GPU. By trading off memory usage against a 20% increase in computation time, we’ve used this to train 10X larger models:https://github.com/openai/gradient-checkpointing …
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Recent Advances in Recurrent Neural Networks (fundamentals, recent advances & research challenges) https://arxiv.org/abs/1801.01078
#MachineLearningpic.twitter.com/pSy3QwGKB1
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Today, we are publishing some Google Assistant evaluation guidelines for those who are researching improvements in voice interactions with technology. It is our hope that they will help the community build and evaluate their own systems. Learn more at →http://goo.gl/sGzkkB
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Learn about Neural Image Assessment (NIMA), a deep CNN that is trained to rate the technical and aesthetic qualities of an image, scoring them reliably and with high correlation to human perception. Oh, and it can be used to enhance images too! → http://goo.gl/wLJF3G pic.twitter.com/TkbUmrlis2
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Very detailed notes of
#NIPS2017 conference. 43 pages from David Abel. https://cs.brown.edu/~dabel/blog/posts/misc/nips_2017.pdf …pic.twitter.com/urrzZZ7cQn
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Yevgeniy Ivanchenko proslijedio/la je Tweet
This one is a very good introduction to the most common building blocks of recent Deep Learning architectures.https://twitter.com/mat_kelcey/status/940324104820756481 …
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Yevgeniy Ivanchenko proslijedio/la je Tweet
The generalization of AlphaGo Zero, called AlphaZero, achieves superhuman performance in all of Chess, Shogi, and Go. Starting from random play, and given no domain knowledge. New paper from DeepMind: https://arxiv.org/abs/1712.01815
Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Yevgeniy Ivanchenko proslijedio/la je Tweet
In order to build better and more robust DNN-based systems, one must be able to effectively interpret the models. We introduce a simple and scalable method to both compare and interpret the representations learned by DNNshttp://goo.gl/jqZgdY
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Introducing Population Based Training: a new method for automatically performing online hyperparameter adaptation and model selection by exploiting populations of neural networks https://deepmind.com/blog/population-based-training-neural-networks/ …pic.twitter.com/4MkIAt1svq
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Yevgeniy Ivanchenko proslijedio/la je Tweet
use gradient magnitude as a signal for gradient importance. Sort your gradients, find a threshold, clip your gradients, exchange sparse gradients, win. https://openreview.net/pdf?id=SkhQHMW0W …pic.twitter.com/sNChdqCCjm
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Today we are announcing SLING, an experimental system for parsing natural language text directly into a representation of its meaning as a semantic frame graph. We hope the research community finds SLING useful! Check it out at http://goo.gl/Ephujt pic.twitter.com/dfNN6D1nKs
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Yevgeniy Ivanchenko proslijedio/la je Tweet
Have you ever wondered what goes on inside
#NeuralNetworks? Learn how@distillpub explores feature visualization at http://goo.gl/7no4XF pic.twitter.com/7ogLg9xWYHHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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