این #پادکست درباره موضوعات big data and data science صحبت می کند. اما موضوعات بحث همیشه واقعا جالب است . https://radar.oreilly.com/tag/oreilly-data-s https://t.iss.one/ArtificialIntelligenceArticles

"Meta-Learning with Temporal Convolutions" by OpenAI https://arxiv.org/abs/1707.03141

"Learning human behaviors from motion capture by adversarial imitation" by DeepMind: for making more natural motions https://arxiv.org/list/cs.LG/pastweek?skip=52&show=25

(#blog) "The Confluence of Geometry and Learning" https://bair.berkeley.edu/blog/2017/07/11/confluence-of-geometry-and-learning/

#FactorNet: Cell Type Transcription Factor. #BigData #DeepLearning #MachineLearning #DataScience #AI #HealthTech
https://buff.ly/2telsnA

New paper explores how agents can learn from unintentional accomplishments https://arxiv.org/pdf/1707.03300.pdf https://t.iss.one/ArtificialIntelligenceArticles

Is Multitask Deep Learning Practical for Pharma? https://doi.org/10.1021/acs.jcim.7b00146 …

#معرفی_محققین_هوش_مصنوعی_در_جهان
Yann LeCun

👁‍🗨#معرفی_محققین_هوش_مصنوعی_در_جهان

🔵4.Yann LeCun

یان LeCun و همکارانش شبکه های عصبی کانولوشه را معرفی کردند . یان مدیر تحقیق AI در فیس بوک است،

همچنین او مدیر موسسه مرکز داده های علمی NYU، استاد در علوم کامپیوتر، علوم عصبی و مهندسی برق و کامپیوتر در NYU است.

یان بر یادگیری ماشین و برنامه های کاربردی آن از جمله بینایی، گفتار، زبان، داده کاوی و بیوانفورماتیک تمرکز دارد. علاوه بر این، یان، بینایی ماشین ، مویایل های رباتیک و علوم اعصاب محاسباتی را مطالعه می کند.


Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Dara Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer Engineering Department.

He received the Electrical Engineer Diploma from Ecole Superieure d'Ingenieurs en Electrotechnique et Electronique (ESIEE), Paris in 1983, and a PhD in Computer Science from Universite Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories in Holmdel, NJ in 1988. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 he directed NYU's initiative in data science and became the founding director of the NYU Center for Data Science. He was named Director of AI Research at Facebook in late 2013 and retains a part-time position on the NYU faculty.

اطلاعات بیشتر

https://yann.lecun.com/ex/index.html

محقق در فیس بوک
https://research.fb.com/people/lecun-yann/

مقالات
https://scholar.google.com/citations?user=WLN3QrAAAAAJ

https://www.researchgate.net/profile/Yann_Lecun

سمینار

https://www.youtube.com/watch?v=IbjF5VjniVE

https://www.youtube.com/watch?v=_1Cyyt-4-n8

https://t.iss.one/ArtificialIntelligenceArticles

"Robust Imitation of Diverse Behaviors" by DeepMind: Improved generative adversarial imitation learning (GAIL) https://arxiv.org/abs/1707.02747 https://t.iss.one/ArtificialIntelligenceArticles

"Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration" https://arxiv.org/abs/1707.02920

7 Best Machine Learning and Deep Learning Courses https://upflow.co/l/PaaV https://t.iss.one/ArtificialIntelligenceArticles

10 Free Must-Read Books for #MachineLearning and #DataScience https://buff.ly/2tenZBu https://t.iss.one/ArtificialIntelligenceArticles

How to turn audio clips into realistic lip-synced video https://grail.cs.washington.edu/projects/AudioToObama/siggraph17_obama.pdf

#خبر

Artificial intelligence helps scientists map behavior in the fruit fly brain | Science | AAAS https://bit.ly/2sUrRox #ai #ml #dl

Neuroevolution: A different kind of deep learning - O'Reilly Media https://bit.ly/2udP3BW #ai #ml #dl https://t.iss.one/ArtificialIntelligenceArticles

🔵Awesome Computer Vision: Awesome

A curated list of awesome computer vision resources, inspired by awesome-php.



https://github.com/jbhuang0604/awesome-computer-vision


🔵Awesome Deep Vision



https://github.com/kjw0612/awesome-deep-vision



🌎Computer Vision Papers with Code

https://github.com/runhani/cv-papers-with-code

🔵Machine Learning for Computer Vision Papers Reading

https://github.com/lizichen/Machine-Learning-For-Computer-Vision

https://t.iss.one/ArtificialIntelligenceArticles

Creatism:A deep-learning photographer capable of creating professional work. https://arxiv.org/abs/1707.03491 https://research.googleblog.com/2017/07/using-deep-learning-to-create.html

CVPR2017 open access: Papers at CVPR2017 are now publicly available https://openaccess.thecvf.com/menu.py https://t.iss.one/ArtificialIntelligenceArticles

Learning Photography Aesthetics w/ Deep CNNs https://arxiv.org/abs/1707.03981 "One Cool Trick" to human-level perf: co-learn 8 visual attributes. #AI