Page Proportions as Musical Intervals
New Codepen by Tero Parviainen : https://codepen.io/teropa/full/xaqzLj/
New Codepen by Tero Parviainen : https://codepen.io/teropa/full/xaqzLj/
Graph Attention Networks
"We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their approximations. By stacking layers in which nodes are able to attend over their neighborhoods' features, we enable (implicitly) specifying different weights to different nodes in a neighborhood, without requiring any kind of costly matrix operation (such as inversion) or depending on knowing the graph structure upfront. (...)"
Paper by Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio : https://arxiv.org/abs/1710.10903
Source Code : https://github.com/PetarV-/GAT
Website : https://mila.quebec/en/publication/graph-attention-networks/
"We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their approximations. By stacking layers in which nodes are able to attend over their neighborhoods' features, we enable (implicitly) specifying different weights to different nodes in a neighborhood, without requiring any kind of costly matrix operation (such as inversion) or depending on knowing the graph structure upfront. (...)"
Paper by Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio : https://arxiv.org/abs/1710.10903
Source Code : https://github.com/PetarV-/GAT
Website : https://mila.quebec/en/publication/graph-attention-networks/
GitHub
GitHub - PetarV-/GAT: Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Graph Attention Networks (https://arxiv.org/abs/1710.10903) - PetarV-/GAT
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Sketch2Code : Turn your whiteboard sketches to working code in seconds
https://azure.microsoft.com/en-us/blog/turn-your-whiteboard-sketches-to-working-code-in-seconds-with-sk
https://azure.microsoft.com/en-us/blog/turn-your-whiteboard-sketches-to-working-code-in-seconds-with-sk
The 50 Best Free Datasets for Machine Learning
https://gengo.ai/articles/the-50-best-free-datasets-for-machine-learning/ @ArtificialIntelligenceArticles
https://gengo.ai/articles/the-50-best-free-datasets-for-machine-learning/ @ArtificialIntelligenceArticles
Five books every data scientist should read that are not about data science
https://towardsdatascience.com/five-books-every-data-scientist-should-read-that-are-not-about-data-science-f7335fb1f84f
https://towardsdatascience.com/five-books-every-data-scientist-should-read-that-are-not-about-data-science-f7335fb1f84f
List of free resources to learn Natural Language Processing
https://blog.paralleldots.com/data-science/nlp/free-natural-language-processing-resources/
https://blog.paralleldots.com/data-science/nlp/free-natural-language-processing-resources/
Lessons from Optics, The Other Deep Learning
https://www.argmin.net/2018/01/25/optics/
https://www.argmin.net/2018/01/25/optics/
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information
paper: https://arxiv.org/abs/1808.10442 @ArtificialIntelligenceArticles
paper: https://arxiv.org/abs/1808.10442 @ArtificialIntelligenceArticles
Deep Learning and the Game of Go
GitHub : https://github.com/maxpumperla/deep_learning_and_the_game_of_go @ArtificialIntelligenceArticles
GitHub : https://github.com/maxpumperla/deep_learning_and_the_game_of_go @ArtificialIntelligenceArticles
RNN to generating beats
Deep Drum using #NeuralNetworks by Gogul Ilango : https://gogul09.github.io/software/deep-drum
Deep Drum using #NeuralNetworks by Gogul Ilango : https://gogul09.github.io/software/deep-drum
Learning where you are looking at (in the browser)
By Max Schumacher : https://cpury.github.io/learning-where-you-are-looking-at/ @ArtificialIntelligenceArticles
By Max Schumacher : https://cpury.github.io/learning-where-you-are-looking-at/ @ArtificialIntelligenceArticles
https://goo.gl/PXZVbE
DeepBayes Summer School 2018
SLIDES, Bayesian Deep Learning
https://deepbayes.ru/#materials
Seminars DeepBayes Summer School Bayesian Deep Learning 2018
https://github.com/bayesgroup/deepbayes-2018
DeepBayes Summer School 2018
Presentations Bayesian Deep Learning
https://drive.google.com/drive/folders/1rJ-HTN3sNTvhJXPoXEEhfGlZWtjNY26C
Vdeos Bayesian Deep Learning
https://www.youtube.com/playlist?list=PLe5rNUydzV9Q01vWCP9BV7NhJG3j7mz62
@ArtificialIntelligenceArticles
DeepBayes Summer School 2018
SLIDES, Bayesian Deep Learning
https://deepbayes.ru/#materials
Seminars DeepBayes Summer School Bayesian Deep Learning 2018
https://github.com/bayesgroup/deepbayes-2018
DeepBayes Summer School 2018
Presentations Bayesian Deep Learning
https://drive.google.com/drive/folders/1rJ-HTN3sNTvhJXPoXEEhfGlZWtjNY26C
Vdeos Bayesian Deep Learning
https://www.youtube.com/playlist?list=PLe5rNUydzV9Q01vWCP9BV7NhJG3j7mz62
@ArtificialIntelligenceArticles
Introducing the Inclusive Images Competition https://ai.googleblog.com/2018/09/introducing-inclusive-images-competition.html
https://goo.gl/zFkc52
Computer science researchers with the highest rate of recent citations
(Google Scholar) among those with the largest h-index Taken among the 100 computer science researchers with the highest Google Scholar h-index(from the list maintained at https://www.guide2research.com/scientists/). Quantities extracted September 1st, 2018.
Yoshua Bengio is now the computer scientist with the most recent citations per day (over the last year), with the top-3 being the deep learning trio, Bengio, Hinton and LeCun, in that order.
Source : https://www.iro.umontreal.ca/~bengioy/citation-rate-CS-1sept2018.html
https://t.iss.one/ArtificialIntelligenceArticles
@ArtificialIntelligenceArticles
Computer science researchers with the highest rate of recent citations
(Google Scholar) among those with the largest h-index Taken among the 100 computer science researchers with the highest Google Scholar h-index(from the list maintained at https://www.guide2research.com/scientists/). Quantities extracted September 1st, 2018.
Yoshua Bengio is now the computer scientist with the most recent citations per day (over the last year), with the top-3 being the deep learning trio, Bengio, Hinton and LeCun, in that order.
Source : https://www.iro.umontreal.ca/~bengioy/citation-rate-CS-1sept2018.html
https://t.iss.one/ArtificialIntelligenceArticles
@ArtificialIntelligenceArticles
A recipe to save lives: Geoffrey Hinton and David Naylor call on physicians to embrace AI
https://goo.gl/rn3usp @ArtificialIntelligenceArticles
https://goo.gl/rn3usp @ArtificialIntelligenceArticles
Machine Learning Top 10 Articles for the Past Month (v.Sep 2018)
https://goo.gl/eaQU5Y @ArtificialIntelligenceArticles
https://goo.gl/eaQU5Y @ArtificialIntelligenceArticles
ML-Agents Toolkit v0.5, new resources for AI researchers available now
https://blogs.unity3d.com/2018/09/11/ml-agents-toolkit-v0-5-new-resources-for-ai-researchers-available-now/
https://blogs.unity3d.com/2018/09/11/ml-agents-toolkit-v0-5-new-resources-for-ai-researchers-available-now/
Unity Technologies Blog
ML-Agents Toolkit v0.5, new resources for AI researchers available now - Unity Technologies Blog
We are committed to working to help make Unity the go-to platform for Artificial Intelligence (AI) research. In the past few weeks, we’ve seen research groups taking notice, with OpenAI using Unity to help train a robot hand to perform a grasping task, and…
All keynotes and AGI conference talks from the Human-Level AI Conference
Enjoy them here: https://slideslive.com/humanlevel-ai-2018
Enjoy them here: https://slideslive.com/humanlevel-ai-2018