No 1. 《The Computational Limits of Deep Learning》
    No 2. 《Learning from Noisy Labels with Deep Neural Networks: A Survey》
    No 3. 《Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop》
    No 4. *《Monte-Carlo Tree Search as Regularized Policy Optimization》
    No 5. 《Towards Deeper Graph Neural Networks》
    No 6. 《Xiaomingbot: A Multilingual Robot News Reporter》
    No 7. *《Unsupervised Shape and Pose Disentanglement for 3D Meshes》
    No 8. *《CheXphoto: 10,000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness》
    No 9. 《Active Learning under Label Shift》
    No 10. 《Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild》
    No 11. 《Generating Person Images with Appearance-aware Pose Stylizer》
    No 12. *《Deep Learning in Protein Structural Modeling and Design》
    No 13. 《Visualizing Deep Graph Generative Models for Drug Discovery》
    No 14. *《Whole-Body Human Pose Estimation in the Wild》
    No 15. 《Shape and Viewpoint without Keypoints》
    No 16. 《ProteiNN: Intrinsic-Extrinsic Convolution and Pooling for Scalable Deep Protein Analysis》
    No 17. *《Contact and Human Dynamics from Monocular Video》
    No 18. 《Generative Hierarchical Features from Synthesizing Images》
    No 19. *《Do Adversarially Robust ImageNet Models Transfer Better?》
    No 20. 《Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop》
    No 21. 《D2D: Learning to find good correspondences for image matching and manipulation》
    No 22. *《CrossTransformers: spatially-aware few-shot transfer》
    No 23. *《A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum》
    No 24. 《TSIT: A Simple and Versatile Framework for Image-to-Image Translation》
    No 25. 《RetrieveGAN: Image Synthesis via Differentiable Patch Retrieval》
    No 26. 《SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design》
    No 27. 《Points2Surf: Learning Implicit Surfaces from Point Cloud Patches》
    No 28. *《Accelerating 3D Deep Learning with PyTorch3D》
    No 29. 《Path Signatures on Lie Groups》
    No 30. 《Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks Via Nonlinear Multigrid》