What’s New in Deep Learning Research: Microsoft’s TextWorld is the OpenAI Gym of Language Learning
https://flipboard.com/@flipboard/-whats-new-in-deep-learning-research-mic/f-2209f1e74e%2Ftowardsdata
https://flipboard.com/@flipboard/-whats-new-in-deep-learning-research-mic/f-2209f1e74e%2Ftowardsdata
Academic Torrents is a distributed system for sharing enormous datasets. So far they have made 27.23TB of research data available. https://academictorrents.com @ArtificialIntelligenceArticles
❄️💦10 مقاله برتر یادگیری ماشین به انتخاب Mybridge در ماه گذشته
Machine Learning Top 10 Articles for the Past Month (v.Aug 2018)
https://goo.gl/DUhd6W @ArtificialIntelligenceArticles
Machine Learning Top 10 Articles for the Past Month (v.Aug 2018)
https://goo.gl/DUhd6W @ArtificialIntelligenceArticles
NVIDIA #Turing
Fusing Real-Time Ray Tracing, AI, Simulation and Rasterization https://goo.gl/fznEeq @ArtificialIntelligenceArticles
Fusing Real-Time Ray Tracing, AI, Simulation and Rasterization https://goo.gl/fznEeq @ArtificialIntelligenceArticles
Deep learning in The Brain : https://goo.gl/oqUXqV @ArtificialIntelligenceArticles
108-page survey paper/book on Deep Learning Techniques for Music Generation. https://arxiv.org/abs/1709.01620
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Video-to-Video Synthesis
Using Conditional GAN to generate HD resolution videos.
paper: https://arxiv.org/abs/1808.06601
Code: https://github.com/NVIDIA/vid2vid
Video: https://goo.gl/c6Em4R
Using Conditional GAN to generate HD resolution videos.
paper: https://arxiv.org/abs/1808.06601
Code: https://github.com/NVIDIA/vid2vid
Video: https://goo.gl/c6Em4R
Set of illustrated Machine Learning cheatsheets covering the content of Stanford's CS 229 class:
Deep Learning: https://goo.gl/nzETEb
Supervised Learning: https://goo.gl/U7UVpj
Unsupervised Learning: https://goo.gl/XgAxk6
Tips and tricks: https://goo.gl/FwwQLP
@ArtificialIntelligenceArticles
Deep Learning: https://goo.gl/nzETEb
Supervised Learning: https://goo.gl/U7UVpj
Unsupervised Learning: https://goo.gl/XgAxk6
Tips and tricks: https://goo.gl/FwwQLP
@ArtificialIntelligenceArticles
stanford.edu
CS 229 - Deep Learning Cheatsheet
Teaching page of Shervine Amidi, Graduate Student at Stanford University.
Pieter Abbeel's slides from his last lecture kicking off the IRIM seminar series yesterday at Georgia Tech
https://www.dropbox.com/s/0cs3s55hsuba0ra/2018_08_13__Deep-Learning-to-Learn__GaTech__Abbeel--final.pdf
@ArtificialIntelligenceArticles
https://www.dropbox.com/s/0cs3s55hsuba0ra/2018_08_13__Deep-Learning-to-Learn__GaTech__Abbeel--final.pdf
@ArtificialIntelligenceArticles
Dropbox
2018_08_13__Deep-Learning-to-Learn__GaTech__Abbeel--final.pdf
Shared with Dropbox
Which GPU(s) to Get for Deep Learning
RTX 2080 most cost-efficient choice. GTX 1080/1070 (+Ti) cards remain very good choices, especially as prices drop
https://goo.gl/97aKSZ
RTX 2080 most cost-efficient choice. GTX 1080/1070 (+Ti) cards remain very good choices, especially as prices drop
https://goo.gl/97aKSZ
Everybody Dance Now
Exciting new work on conditional video synthesis from Berkeley.
"Method for motion transfer: given a video of a person dancing we can transfer that performance to a novel target after only a few min of the target performing standard moves"
https://www.youtube.com/watch?v=PCBTZh41Ris&feature=youtu.be&t=2m14s
paper : https://arxiv.org/abs/1808.07371
@ArtificialIntelligenceArticles
Exciting new work on conditional video synthesis from Berkeley.
"Method for motion transfer: given a video of a person dancing we can transfer that performance to a novel target after only a few min of the target performing standard moves"
https://www.youtube.com/watch?v=PCBTZh41Ris&feature=youtu.be&t=2m14s
paper : https://arxiv.org/abs/1808.07371
@ArtificialIntelligenceArticles
YouTube
Everybody Dance Now
Full paper - https://arxiv.org/pdf/1808.07371.pdf
Deep Learning based object detector #YOLOv3 with OpenCV
With code in both #Python and #C++
https://www.learnopencv.com/deep-learning-based-object-detection-using-yolov3-with-opencv-python-c/
@ArtificialIntelligenceArticles
With code in both #Python and #C++
https://www.learnopencv.com/deep-learning-based-object-detection-using-yolov3-with-opencv-python-c/
@ArtificialIntelligenceArticles
LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
YOLOv3 – Deep Learning Based Object Detection – YOLOv3 with OpenCV ( Python / C++ )
In this post, we will understand what is Yolov3 and learn how to use YOLOv3 — a state-of-the-art object detector — with OpenCV. YOLOv3 is the latest variant of a popular object detection algorithm YOLO – You Only Look Once. The published model recognizes…
A very good article for Reinforcement Learning https://goo.gl/twLP7Y @ArtificialIntelligenceArticles
The Matrix Calculus You Need For Deep Learning
https://explained.ai/matrix-calculus/index.html
@ArtificialIntelligenceArticles
https://explained.ai/matrix-calculus/index.html
@ArtificialIntelligenceArticles
What You Need to Know Before Considering a PhD
If you're considering a PhD, go read this excellent post by Rachel Thomas /
https://goo.gl/eqRRDy @ArtificialIntelligenceArticles
If you're considering a PhD, go read this excellent post by Rachel Thomas /
https://goo.gl/eqRRDy @ArtificialIntelligenceArticles
Evaluating Theory of Mind in Question Answering
https://arxiv.org/abs/1808.09352 @ArtificialIntelligenceArticles
https://arxiv.org/abs/1808.09352 @ArtificialIntelligenceArticles
In this Viewpoint, Geoffrey Hinton of Google’s Brain Team discusses the basics of neural networks. Learn more https://goo.gl/mmAiX8 @ArtificialIntelligenceArticles
Deep learning for predicting aftershocks of large earthquakes.
Besides offering better predictions, interpretations of the model suggest promising directions for new physical theories
https://www.nature.com/articles/s41586-018-0438-y
The success of artificial intelligence in this domain is thanks to one of the technology’s core strengths: its ability to uncover previously overlooked patterns in complex datasets. This is especially relevant in seismology, where it can be incredibly difficult to see connections in the data. Seismic events involve too many variables, from the makeup of the ground in different areas to the types of interactions between seismic plates to the ways energy propagates in waves through the Earth. Making sense of it all is incredibly hard.
The researchers say their deep learning model was able to make its predictions by considering a factor known as the “von Mises yield criterion,” a complex calculation used to predict when materials will begin to break under stress.
https://t.iss.one/ArtificialIntelligenceArticles
Besides offering better predictions, interpretations of the model suggest promising directions for new physical theories
https://www.nature.com/articles/s41586-018-0438-y
The success of artificial intelligence in this domain is thanks to one of the technology’s core strengths: its ability to uncover previously overlooked patterns in complex datasets. This is especially relevant in seismology, where it can be incredibly difficult to see connections in the data. Seismic events involve too many variables, from the makeup of the ground in different areas to the types of interactions between seismic plates to the ways energy propagates in waves through the Earth. Making sense of it all is incredibly hard.
The researchers say their deep learning model was able to make its predictions by considering a factor known as the “von Mises yield criterion,” a complex calculation used to predict when materials will begin to break under stress.
https://t.iss.one/ArtificialIntelligenceArticles
Nature
Deep learning of aftershock patterns following large earthquakes
Nature - Neural networks trained on data from about 130,000 aftershocks from around 100 large earthquakes improve predictions of the spatial distribution of aftershocks and suggest physical...
The p5.js Web Editor is a friendly online platform for learning to code in a visual way. Designed for all ages and abilities, anyone can get started quickly creating, editing, https://goo.gl/3TLZrU