Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control
Christian Schroeder de Witt et al.: https://arxiv.org/abs/2003.06709
#MachineLearning #ArtificialIntelligence #ReinforcementLearning
Christian Schroeder de Witt et al.: https://arxiv.org/abs/2003.06709
#MachineLearning #ArtificialIntelligence #ReinforcementLearning
CS472 Data science and AI for COVID-19
Zou et al.: https://sites.google.com/view/data-science-covid-19/
#ArtificialIntelligence #Covid19 #DataScience https://t.iss.one/ArtificialIntelligenceArticles
Zou et al.: https://sites.google.com/view/data-science-covid-19/
#ArtificialIntelligence #Covid19 #DataScience https://t.iss.one/ArtificialIntelligenceArticles
Lucid
A collection of infrastructure and tools for research in neural network interpretability : https://github.com/tensorflow/lucid
#Tensorflow #Interpretability #Visualization #MachineLearning #Colab
A collection of infrastructure and tools for research in neural network interpretability : https://github.com/tensorflow/lucid
#Tensorflow #Interpretability #Visualization #MachineLearning #Colab
GitHub
GitHub - tensorflow/lucid: A collection of infrastructure and tools for research in neural network interpretability.
A collection of infrastructure and tools for research in neural network interpretability. - tensorflow/lucid
New open source dataset for abstractive summarisation
https://medium.com/curation-corporation/teaching-an-ai-to-abstract-a-new-dataset-for-abstractive-auto-summarisation-5227f546caa8
https://medium.com/curation-corporation/teaching-an-ai-to-abstract-a-new-dataset-for-abstractive-auto-summarisation-5227f546caa8
Medium
Teaching an AI to summarise news articles: A new dataset for abstractive summarisation
Curation is open-sourcing 40,000 professionally-written summaries of articles, along with code to build your own AI abstractive summariser.
Representation Learning Through Latent Canonicalizations
Litany et al.: https://arxiv.org/abs/2002.11829
#ArtificialIntelligence #DeepLearning #RepresentationLearning
Litany et al.: https://arxiv.org/abs/2002.11829
#ArtificialIntelligence #DeepLearning #RepresentationLearning
Unboxing the "Black Box": Learning Interpretable Deep Learning Features of Brain Aging
https://prism.ucalgary.ca/handle/1880/111255
https://prism.ucalgary.ca/handle/1880/111255
Corona Virus Media Watch launched by UNESCO’s International Research Centre on Artificial Intelligence in Slovenia
https://videolectures.net/site/news/corona_live/
https://t.iss.one/ArtificialIntelligenceArticles
https://videolectures.net/site/news/corona_live/
https://t.iss.one/ArtificialIntelligenceArticles
Help us scale #COVID19 detection over the phone.
If you have a #COVID19 diagnosis or are healthy, consider recording a breathing sample anonymously at
https://www.breatheforscience.com/
We hope this data leads to techniques to help diagnosis of #COVID19 over the phone.
If you have a #COVID19 diagnosis or are healthy, consider recording a breathing sample anonymously at
https://www.breatheforscience.com/
We hope this data leads to techniques to help diagnosis of #COVID19 over the phone.
Breathe for science
NYU study to help scale covid19 diagnosis over the phone. Simply record your breathing anonymously to participate.
Gradient Boosting Neural Networks: GrowNet
Badirli et al.: https://arxiv.org/abs/2002.07971v1
#ArtificialIntelligence #GradientBoosting #NeuralNetworks
Badirli et al.: https://arxiv.org/abs/2002.07971v1
#ArtificialIntelligence #GradientBoosting #NeuralNetworks
Backpropagation, Intuitions (Stanford CS231n)
Link: https://cs231n.github.io/optimization-2/
Link: https://cs231n.github.io/optimization-2/
cs231n.github.io
CS231n Deep Learning for Computer Vision
Course materials and notes for Stanford class CS231n: Deep Learning for Computer Vision.
Generalizable Autonomy for Robot Manipulation https://www.youtube.com/watch?v=8Kn4Gi8iSYQ
YouTube
MIT 6.S191 (2020): Generalizable Autonomy for Robot Manipulation
MIT Introduction to Deep Learning 6.S191: Lecture 8
Generalizable Autonomy for Robot Manipulation
Lecturer: Animesh Garg (NVIDIA & University of Toronto)
January 2020
For all lectures, slides, and lab materials: https://introtodeeplearning.com
Lecture Outline…
Generalizable Autonomy for Robot Manipulation
Lecturer: Animesh Garg (NVIDIA & University of Toronto)
January 2020
For all lectures, slides, and lab materials: https://introtodeeplearning.com
Lecture Outline…
Understanding the limits of convolutional neural networks — one of AI’s greatest achievements
https://thenextweb.com/neural/2020/03/20/understanding-the-limits-of-convolutional-neural-networks-one-of-ais-greatest-achievements-syndication/
https://thenextweb.com/neural/2020/03/20/understanding-the-limits-of-convolutional-neural-networks-one-of-ais-greatest-achievements-syndication/
Neural | The Next Web
Understanding the limits of convolutional neural networks — one of AI’s greatest achievements
After a prolonged winter, artificial intelligence is experiencing a scorching summer mainly thanks to advances in deep learning and artificial neural networks. To be more precise, the renewed interest in deep learning is largely due to the success of convolutional…
MIT offers free video lectures and online materials from more than 2,400 courses, including intro classes in computer science, AI and algorithms.
Browse our open CS courses here:
https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/
Browse our open CS courses here:
https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/
MIT OpenCourseWare
Search | MIT OpenCourseWare | Free Online Course Materials
MIT OpenCourseWare is a web based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity
"Learning Object Permanence from Video"
Aviv Shamsian et al.: https://arxiv.org/abs/2003.10469
Website: https://chechiklab.biu.ac.il/~avivshamsian/OP/OP_HTML.html
Github: https://github.com/ofrikleinfeld/ObjectPermanence
#ArtificialIntelligence #DeepLearning #MachineLearning
Aviv Shamsian et al.: https://arxiv.org/abs/2003.10469
Website: https://chechiklab.biu.ac.il/~avivshamsian/OP/OP_HTML.html
Github: https://github.com/ofrikleinfeld/ObjectPermanence
#ArtificialIntelligence #DeepLearning #MachineLearning
Deep reinforcement learning for de novo drug design
Popova et al.: https://advances.sciencemag.org/content/4/7/eaap7885
Code:
https://t.iss.one/ArtificialIntelligenceArticles
https://github.com/isayev/ReLeaSE
#Covid19Response #DeepLearning #ReinforcementLearning
Popova et al.: https://advances.sciencemag.org/content/4/7/eaap7885
Code:
https://t.iss.one/ArtificialIntelligenceArticles
https://github.com/isayev/ReLeaSE
#Covid19Response #DeepLearning #ReinforcementLearning
Science Advances
Deep reinforcement learning for de novo drug design
We have devised and implemented a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcement Learning for Structural Evolution). On the basis of deep and reinforcement learning (RL) approaches, ReLeaSE…