No 1. 《Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator》
    No 2. 《Graph Transformer Networks》
    No 3. 《Representation Learning: A Statistical Perspective》
    No 4. 《Bayesian forecasting of multivariate time series: Scalability, structure uncertainty and decisions》
    No 5. 《AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks》
    No 6. 《Image2StyleGAN++: How to Edit the Embedded Images?》
    No 7. 【哎呀！视频里的意外行为检测】
    No 8. 《TimeCaps: Capturing Time Series Data with Capsule Networks》
    No 9. 《Semantic Bottleneck Scene Generation》
    No 10. 《SuperGlue: Learning Feature Matching with Graph Neural Networks》
    No 11. 《Learning to Communicate in Multi-Agent Reinforcement Learning : A Review》
    No 12. 《Causality for Machine Learning》
    No 13. 《Active Learning for Deep Detection Neural Networks》
    No 14. 《Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding》
    No 15. 《Differentiable Convex Optimization Layers》
    No 16. 《Deep Motion Blur Removal Using Noisy/Blurry Image Pairs》
    No 17. 《Instance Cross Entropy for Deep Metric Learning》
    No 18. 《How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions》
    No 19. 《Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis》
    No 20. 《Bayesian interpretation of SGD as Ito process》
    No 21. 《Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering》
    No 22. 《Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild》
    No 23. 《Parallelising MCMC via Random Forests》
    No 24. 《Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach》
    No 25. 《Towards a complete 3D morphable model of the human head》
    No 26. 《Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models》
    No 27. 《Compressing Representations for Embedded Deep Learning》
    No 28. 《Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting》
    No 29. 《Object-Guided Instance Segmentation for Biological Images》
    No 30. 《Noise Robust Generative Adversarial Networks》