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for who have a passion for -
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
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5. #Neuroscience

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SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
Fedorov et al.: https://arxiv.org/pdf/1905.12107.pdf
#ArtificialIntelligence #DeepLearning #MachineLearning
Our CVPR'19 paper about neural free-viewpoint rendering of human avatars without reconstructing geometry is on arXiv! Generator predicts UV mapping (not RGB), and texture is learned per-avatar.

🌐 (link: https://saic-violet.github.io/texturedavatar) saic-violet.github.io/texturedavatar
▶️ (link: https://youtu.be/3rrnUX8wWZ8) youtu.be/3rrnUX8wWZ8
📝 (link: https://arxiv.org/abs/1905.08776) arxiv.org/abs/1905.08776
Speech2Face: Learning the Face Behind a Voice #CVPR2019



ArXiv
arxiv.org/abs/1905.09773
Project
speech2face.github.io
Image Alignment in Unseen Domains via Domain Deep Generalization. arxiv.org/abs/1905.12028
Incidence Networks for Geometric Deep Learning. arxiv.org/abs/1905.11460
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
Kohl et al.: https://arxiv.org/abs/1905.13077
#ArtificialIntelligence #DeepLearning #MachineLearning
Autonomous skill discovery with Quality-Diversity and Unsupervised Descriptors
Cully et al.: https://arxiv.org/pdf/1905.11874.pdf
#QualityDiversity #Optimization #Evolution #Robotics #DeepLearning
Practical Full Resolution Learned Lossless Image Compression
Mentzer et al.: https://arxiv.org/abs/1811.12817
PyTorch Implementation: https://github.com/fab-jul/L3C-PyTorch
#deeplearning #machinelearning #pytorch #technology