A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs
Paper https://arxiv.org/abs/1901.00945
#Neurons #Cognition #MachineLearning
Paper https://arxiv.org/abs/1901.00945
#Neurons #Cognition #MachineLearning
IBM Research Releases ‘Diversity in Faces’ Dataset to Advance Study of Fairness in Facial Recognition Systems
Blog by John R. Smith: https://www.ibm.com/blogs/research/2019/01/diversity-in-faces/
Blog by John R. Smith: https://www.ibm.com/blogs/research/2019/01/diversity-in-faces/
What are Symbolic and Imperative APIs in TensorFlow 2.0?
https://medium.com/tensorflow/what-are-symbolic-and-imperative-apis-in-tensorflow-2-0-dfccecb01021
https://medium.com/tensorflow/what-are-symbolic-and-imperative-apis-in-tensorflow-2-0-dfccecb01021
FaceForensics++: Learning to Detect Manipulated Facial Images
Paper by Rössler et al.: https://arxiv.org/abs/1901.08971
Paper by Rössler et al.: https://arxiv.org/abs/1901.08971
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Paper by Nicolas Papernot, Patrick McDaniel: https://arxiv.org/abs/1803.04765
Code: https://github.com/tensorflow/cleverhans/tree/master/cleverhans/model_zoo/deep_k_nearest_neighbors
Paper by Nicolas Papernot, Patrick McDaniel: https://arxiv.org/abs/1803.04765
Code: https://github.com/tensorflow/cleverhans/tree/master/cleverhans/model_zoo/deep_k_nearest_neighbors
VeGANs
A library to easily train various existing GANs (Generative Adversarial Networks) in PyTorch: https://github.com/unit8co/vegans
#pytorch #GAN #GenerativeAdversarialNetworks #MachineLearning
A library to easily train various existing GANs (Generative Adversarial Networks) in PyTorch: https://github.com/unit8co/vegans
#pytorch #GAN #GenerativeAdversarialNetworks #MachineLearning
Amazing Machine Learning Open Source of the Year (v.2019)
https://medium.mybridge.co/amazing-machine-learning-open-source-tools-projects-of-the-year-v-2019-95d772e4e985
https://medium.mybridge.co/amazing-machine-learning-open-source-tools-projects-of-the-year-v-2019-95d772e4e985
So many papers applying deep learning to theoretical and experimental physics!
Fascinating.
https://physicsml.github.io/pages/papers.html
Fascinating.
https://physicsml.github.io/pages/papers.html
Machine Learning Papers with Code - A searchable site that links machine learning papers on ArXiv with code on GitHub https://paperswithcode.com/ @ArtificialIntelligenceArticles
Lex Fridman :
New introductory lecture of the MIT Self-Driving Cars series with an overview of the industry from Tesla to Waymo and autonomous taxi services to flying cars and connected vehicles to human-centered autonomy. Many interesting talks to come!
https://www.youtube.com/watch?v=sRxaMDDMWQQ
New introductory lecture of the MIT Self-Driving Cars series with an overview of the industry from Tesla to Waymo and autonomous taxi services to flying cars and connected vehicles to human-centered autonomy. Many interesting talks to come!
https://www.youtube.com/watch?v=sRxaMDDMWQQ
YouTube
Self-Driving Cars: State of the Art (2019)
Introductory lecture of the MIT Self-Driving Cars series (6.S094) with an overview of the autonomous vehicle industry in 2018 and looking forward to 2019, including Waymo, Tesla, Cruise, Ford, GM, and out-of-the-box ideas of boring tunnels, flying cars, connected…
The power of deeper networks for expressing natural functions”,
Rolnick and Tegmark: https://arxiv.org/abs/1705.05502
#artificalintelligence #deeplearning #machinelearning
Rolnick and Tegmark: https://arxiv.org/abs/1705.05502
#artificalintelligence #deeplearning #machinelearning
AAAI Conference Analytics
Citation distribution by the top AAAI 20 authors, year by year:https://goo.gl/Z15LbW
#artificalintelligence #deeplearning #machinelearning
Citation distribution by the top AAAI 20 authors, year by year:https://goo.gl/Z15LbW
#artificalintelligence #deeplearning #machinelearning
Lex Fridman : First blog post on Deep Learning Basics with TensorFlow (on the official TensorFlow page):
https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0
https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0
The Hanabi Challenge: A New Frontier for AI Research
Paper by Bard et al.: https://arxiv.org/abs/1902.00506
Code: https://github.com/deepmind/hanabi-learning-environment
Paper by Bard et al.: https://arxiv.org/abs/1902.00506
Code: https://github.com/deepmind/hanabi-learning-environment
Can neural networks learn commonsense reasoning?
ATOMIC | An Atlas of Machine Commonsense for If-Then Reasoning: https://homes.cs.washington.edu/~msap/atomic/
ATOMIC | An Atlas of Machine Commonsense for If-Then Reasoning: https://homes.cs.washington.edu/~msap/atomic/
Neuroscience-Inspired Artificial Intelligence
https://www.cell.com/neuron/pdf/S0896-6273(17)30509-3.pdf @ArtificialIntelligenceArticles
https://www.cell.com/neuron/pdf/S0896-6273(17)30509-3.pdf @ArtificialIntelligenceArticles
New interesting paper in Super Resolution area https://arxiv.org/abs/1812.04240
arXiv.org
Unsupervised Degradation Learning for Single Image Super-Resolution
Deep Convolution Neural Networks (CNN) have achieved significant performance
on single image super-resolution (SR) recently. However, existing CNN-based
methods use artificially synthetic...
on single image super-resolution (SR) recently. However, existing CNN-based
methods use artificially synthetic...
Organic computers may be our future https://phys.org/news/2018-12-amoeba-approximate-solutions-np-hard-problem.html
phys.org
Amoeba finds approximate solutions to NP-hard problem in linear time
Researchers have demonstrated that an amoeba—a single-celled organism consisting mostly of gelatinous protoplasm—has unique computing abilities that may one day offer a competitive alternative to ...
Good course from Stanford "Human behavior biology"
https://tjournal.ru/science/84155-vse-25-lekciy-stenfordskogo-kursa-professora-roberta-sapolski-biologiya-povedeniya-cheloveka
https://tjournal.ru/science/84155-vse-25-lekciy-stenfordskogo-kursa-professora-roberta-sapolski-biologiya-povedeniya-cheloveka
TJ
Все 25 лекций Стэнфордского курса профессора Роберта Сапольски «Биология поведения человека» — Наука на TJ
Сексуальное поведение, генетика, шизофрения и многое другое в 25 лекциях курса профессора Роберта Сапольски «Биология поведения человека» на русском языке!