爱可可老师一周论文精选(2019.7.28)

No 1. 《Time2Vec: Learning a Vector Representation of Time》
No 2. 《SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications》
No 3. 《Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function》
No 4. 《Techniques for Automated Machine Learning》
No 5. 《A Baseline for 3D Multi-Object Tracking》
No 6. 《MixNet: Mixed Depthwise Convolutional Kernels》
No 7. 《Pairwise Link Prediction》
No 8. 《Quant GANs: Deep Generation of Financial Time Series》
No 9. 《Green AI》
No 10. 《Deep-SLAM++: Object-level RGBD SLAM based on class-specific deep shape priors》
No 11. 《NPA: Neural News Recommendation with Personalized Attention》
No 12. 《OmniNet: A unified architecture for multi-modal multi-task learning》
No 13. 《Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation》
No 14. 《Faster Neural Network Training with Data Echoing》
No 15. 《Image-and-Spatial Transformer Networks for Structure-Guided Image Registration》
No 16. 《Bayesian Inference with Generative Adversarial Network Priors》
No 17. 《Noise Contrastive Variational Autoencoders》
No 18. 《Understanding Video Content: Efficient Hero Detection and Recognition for the Game 'Honor of Kings'》
No 19. 《U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation》
No 20. 《Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images》
No 21. 《Spectral Analysis of Latent Representations》
No 22. 《IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification》
No 23. 《An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments》
No 24. 《Differentiable Bayesian Neural Network Inference for Data Streams》
No 25. 《Trusses and Trapezes: Easily-Interpreted Communities in Social Networks》
No 26. 《Y-Autoencoders: disentangling latent representations via sequential-encoding》
No 27. 《Convolutional Neural Networks on Randomized Data》
No 28. 《Learning to Select, Track, and Generate for Data-to-Text》
No 29. 《Hierarchical Sequence to Sequence Voice Conversion with Limited Data》
No 30. 《Statistical data analysis in the Wasserstein space》

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