AI, Python, Cognitive Neuroscience – Telegram
AI, Python, Cognitive Neuroscience
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"Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer (POET)"

Slides by Jeff Clune: https://lnkd.in/ePpcNQS

#neuroevolution #evolutionstrategy #machinelearning

✴️ @AI_Python_EN
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A deep learning model developed by NVIDIA Research turns rough doodles into highly realistic scenes using generative adversarial networks (GANs). Dubbed GauGAN, the tool is like a smart paintbrush, converting segmentation maps into lifelike images.

#GAN #deeplearning

✴️ @AI_Python_EN
When the paper you’re reading keeps citing another paper.

#deeplearning #jokes
✴️ @AI_Python_EN
article on Machine learning got published in Better Programming on Medium
https://medium.com/better-programming/from-machine-learning-to-reinforcement-learning-mastery-47f33d9f6b41

Feedback welcome!

✴️ @AI_Python_EN
APS Physics Viewpoint on 4 independent works on Neural Network Variational Methods for Open Quantum Systems!
https://physics.aps.org/articles/v12/74

✴️ @AI_Python_EN
Convolutional #NeuralNetworks (CNN) for Image Classification — a step by step illustrated tutorial: https://dy.si/hMqCH
BigData #AI #MachineLearning #ComputerVision #DataScientists #DataScience #DeepLearning #Algorithms

✴️ @AI_Python_EN
Modern machine learning is driven by building good environments/datasets. We’ve just open-sourced a tool we created for rendering high-quality synthetic robotics data:
OpenAI : We're releasing ORRB (OpenAI Remote Rendering Backend)—a Unity3d-based system that enables rapid and customizable renderings of robotics environments.
Paper: https://arxiv.org/abs/1906.11633
Code: https://github.com/openai/orrb

✴️ @AI_Python_EN
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds
arxiv.org/abs/1805.06299

#NLP #MachineLearning #DeepLearning

✴️ @AI_Python_EN
Skill from Video data + motion reconstruction
code: https://github.com/akanazawa/motion_reconstruction
CVPR'19 human motion paper training
code: https://github.com/akanazawa/human_dynamics

✴️ @AI_Python_EN