爱可可老师一周论文精选(2018.12.1)

No 1. 【基因组学深度学习入门】
No 2. 【视觉常识推理(VCR)】
No 3. 《Smooth Loss Functions for Deep Top-k Classification》
No 4. 《Dataset Distillation》
No 5. 《Weakly Supervised Semantic Image Segmentation with Self-correcting Networks》
No 6. 【用于视频超分辨率的时间相干GAN(TecoGAN)】
No 7. 《Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector》
No 8. 《How Many Samples are Needed to Learn a Convolutional Neural Network?》
No 9. 《Do GAN Loss Functions Really Matter?》
No 10. 《Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos》
No 11. 《One-Shot Instance Segmentation》
No 12. 《ML-Net: multi-label classification of biomedical texts with deep neural networks》
No 13. 《Partial Convolution based Padding》
No 14. 《Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving》
No 15. 《DynamicGEM: A Library for Dynamic Graph Embedding Methods》
No 16. 《Matching Features without Descriptors: Implicitly Matched Interest Points (IMIPs)》
No 17. 《Perturbative Neural Networks》
No 18. 《Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models》
No 19. 【人形机器人分级视觉运动控制】
No 20. 《Guiding the One-to-one Mapping in CycleGAN via Optimal Transport》
No 21. 《Scalable Logo Recognition using Proxies》
No 22. 《Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting》
No 23. 《Exploiting Sentence Embedding for Medical Question Answering》
No 24. 《An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss》
No 25. 《Understanding the impact of entropy in policy learning》
No 26. 《A Sufficient Condition for Convergences of Adam and RMSProp》
No 27. 《Sentence Encoding with Tree-constrained Relation Networks》
No 28. 《LinkNet: Relational Embedding for Scene Graph》
No 29. 《Is Data Clustering in Adversarial Settings Secure?》
No 30. 《Understanding and Measuring Psychological Stress using Social Media》

发表评论

电子邮件地址不会被公开。 必填项已用*标注