ThunderNet: Towards Real-time Generic Object Detection
https://arxiv.org/pdf/1903.11752v1.pdf
https://arxiv.org/pdf/1903.11752v1.pdf
Jetson Nano š
NVIDIA Jetson Nano enables the development of new small, low-power AI systems. It opens new worlds of embedded IoT applications, including home robots.
It's a small AI computer to create intelligent systems:https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-nano/
#ArtificialIntelligence #DeepLearning #MachineLearning #ReinforcementLearning #Robotics
NVIDIA Jetson Nano enables the development of new small, low-power AI systems. It opens new worlds of embedded IoT applications, including home robots.
It's a small AI computer to create intelligent systems:https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-nano/
#ArtificialIntelligence #DeepLearning #MachineLearning #ReinforcementLearning #Robotics
Attention in RNNs: Understanding the mechanism with a detailed example #DeepLearning
https://medium.com/datadriveninvestor/attention-in-rnns-321fbcd64f05
https://medium.com/datadriveninvestor/attention-in-rnns-321fbcd64f05
Medium
Attention in RNNs
Understanding the mechanism with a detailed example
āNip Fake News in the bud: Introducing PreFakesā by UnFound
https://medium.com/unfound-news/nip-fake-news-in-the-bud-introducing-prefakes-69f768af2dc6
https://medium.com/unfound-news/nip-fake-news-in-the-bud-introducing-prefakes-69f768af2dc6
Reversible Adversarial Examples
Liu et al.: https://arxiv.org/abs/1811.00189
#ComputerVision #PatternRecognition #MachineLearning #MontrƩalAI #NeuralNetworks
Liu et al.: https://arxiv.org/abs/1811.00189
#ComputerVision #PatternRecognition #MachineLearning #MontrƩalAI #NeuralNetworks
Machine learning and artificial intelligence in the quantum domain"
By Vedran Dunjko, Hans J. Briegel: https://arxiv.org/abs/1709.02779
#QuantumPhysics #ArtificialIntelligence #ComputerVision #MontrealAI #PatternRecognition
By Vedran Dunjko, Hans J. Briegel: https://arxiv.org/abs/1709.02779
#QuantumPhysics #ArtificialIntelligence #ComputerVision #MontrealAI #PatternRecognition
StrokeNet: A Neural Painting Environment
Zheng et al.: https://openreview.net/forum?id=HJxwDiActX
#imagegeneration #differentiablemodel #reinforcementlearning #deeplearning #modelbased
Zheng et al.: https://openreview.net/forum?id=HJxwDiActX
#imagegeneration #differentiablemodel #reinforcementlearning #deeplearning #modelbased
Image search using multilingual texts: a cross-modal learning approach between image and text Maxime Portaz Qwant Research
https://arxiv.org/abs/1903.11299
https://arxiv.org/abs/1903.11299
arXiv.org
Image search using multilingual texts: a cross-modal learning...
Multilingual (or cross-lingual) embeddings represent several languages in a unique vector space. Using a common embedding space enables for a shared semantic between words from different...
Deep Neural Networks Improve Radiologistsā Performance in Breast Cancer Screening
https://medium.com/@jasonphang/deep-neural-networks-improve-radiologists-performance-in-breast-cancer-screening-565eb2bd3c9f ArXiV: https://arxiv.org/abs/1903.08297
GitHub (code & models): https://github.com/nyukat/breast_cancer_classifier
https://medium.com/@jasonphang/deep-neural-networks-improve-radiologists-performance-in-breast-cancer-screening-565eb2bd3c9f ArXiV: https://arxiv.org/abs/1903.08297
GitHub (code & models): https://github.com/nyukat/breast_cancer_classifier
DeepMindAI: Today we're releasing a large-scale extendable dataset of mathematical questions, for training (and evaluating the abilities of) neural models that can reason algebraically.
Paper: https://arxiv.org/abs/1904.01557 Code and data : https://github.com/deepmind/mathematics_dataset
Paper: https://arxiv.org/abs/1904.01557 Code and data : https://github.com/deepmind/mathematics_dataset
Learning Discrete Structures for Graph Neural Networks
Franceschi et al.: https://arxiv.org/abs/1903.11960
#DeepLearning #MachineLearning #NeuralNetworks
Franceschi et al.: https://arxiv.org/abs/1903.11960
#DeepLearning #MachineLearning #NeuralNetworks
Climate change: How can AI help?
Applying machine learning to address the problems of climate change.
Call For Submissions: https://www.climatechange.ai
#artificialintelligence #climatechange #machinelearning
Applying machine learning to address the problems of climate change.
Call For Submissions: https://www.climatechange.ai
#artificialintelligence #climatechange #machinelearning
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HoloGAN: Unsupervised learning of 3D representations from natural images.
Another demonstration that hardcoding prior knowledge about the world is generally a good idea.
Blog: https://www.monkeyoverflow.com/#/hologan-unsupervised-learning-of-3d-representations-from-natural-images/
Paper: https://arxiv.org/abs/1904.01326
Another demonstration that hardcoding prior knowledge about the world is generally a good idea.
Blog: https://www.monkeyoverflow.com/#/hologan-unsupervised-learning-of-3d-representations-from-natural-images/
Paper: https://arxiv.org/abs/1904.01326
A review of INFINITE POWERS in nature: From counting with stones to artificial intelligence: the story of calculus. Anil Ananthaswamy savours a history of the mathematics used to track changes in everything from DNA to machine learning.
https://www.nature.com/articles/d41586-019-01038-4
https://www.nature.com/articles/d41586-019-01038-4
Nature
From counting with stones to artificial intelligence: the story of calculus
Nature - Anil Ananthaswamy savours a history of the mathematics used to track changes in everything from DNA to machine learning.
Father of GANs Ian Goodfellow @goodfellow_ian Splits Google For Apple
https://syncedreview.com/2019/04/04/father-of-gans-ian-goodfellow-splits-google-for-apple/
https://syncedreview.com/2019/04/04/father-of-gans-ian-goodfellow-splits-google-for-apple/
Synced
Father of GANs Ian Goodfellow Splits Google For Apple
Ian Goodfellow ā the research scientist who pioneered generative adversarial networks (GANs) ā has left Google Brain and joined Apple to direct a special machine learning project, according to his ā¦