No 1. 《On the Relationship between Self-Attention and Convolutional Layers》
No 2. 《Deep Learning for Stock Selection Based on High Frequency Price-Volume Data》
No 3. 《Confident Learning: Estimating Uncertainty in Dataset Labels》
No 4. 《Adversarial Fisher Vectors for Unsupervised Representation Learning》
No 5. 《Stacked Capsule Autoencoders》
No 6. 《Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research》
No 7. 《Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation》
No 8. 《Document-level Neural Machine Translation with Inter-Sentence Attention》
No 9. 《Recurrent Neural Network Transducer for Audio-Visual Speech Recognition》
No 10. 《The Measure of Intelligence》
No 11. 《Information Bottleneck Methods on Convolutional Neural Networks》
No 12. 《This dataset does not exist: training models from generated images》
No 13. 《How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods》
No 14. 《Probing the robustness of nested multi-layer networks》
No 15. 《Conversation Generation with Concept Flow》
No 16. 《DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning》
No 17. 《Self-training with Noisy Student improves ImageNet classification》
No 18. 《MLPerf Inference Benchmark》
No 19. 《What Do We Really Need? Degenerating U-Net on Retinal Vessel Segmentation》
No 20. 《Learning Internal Representations》
No 21. 《Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods》
No 22. 《HDBSCAN(ε̂ ): An Alternative Cluster Extraction Method for HDBSCAN》
No 23. 《CartoonRenderer: An Instance-based Multi-Style Cartoon Image Translator》
No 24. 《Modern Neural Networks Generalize on Small Data Sets》
No 25. 《360SD-Net: 360° Stereo Depth Estimation with Learnable Cost Volume》
No 26. 《Designing neural networks through neuroevolution | Nature Machine Intelligence》
No 27. 《Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models》
No 28. 《Nonlinearity + Networks: A 2020 Vision》
No 29. 《Emerging Cross-lingual Structure in Pretrained Language Models》
No 30. 《Evaluating Combinatorial Generalization in Variational Autoencoders》