No 1. 《Object Detection in 20 Years: A Survey》
No 2. 【视频三维人体动态学习】
No 3. 《Learning Embeddings into Entropic Wasserstein Spaces》
No 4. 《Bayesian Optimization using Deep Gaussian Processes》
No 5. 《Embedding Human Knowledge in Deep Neural Network via Attention Map》
No 6. 《D2-Net: A Trainable CNN for Joint Detection and Description of Local Features》
No 7. 《Graph U-Nets》
No 8. 《Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks》
No 9. 《Graph Convolutional Gaussian Processes》
No 10. 《Targeted Sentiment Analysis: A Data-Driven Categorization》
No 11. 《S4L: Self-Supervised Semi-Supervised Learning》
No 12. 《Learning Loss for Active Learning》
No 13. 《Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting》
No 14. 《MASS: Masked Sequence to Sequence Pre-training for Language Generation》
No 15. 【人体姿态可学习三角测量】
No 16. 《Zero-Shot Voice Style Transfer with Only Autoencoder Loss》
No 17. 《Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs》
No 18. 《Meta-Learning with Differentiable Convex Optimization》
No 19. 《MeshCNN: A Network with an Edge》
No 20. 《Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping》
No 21. 《RadiX-Net: Structured Sparse Matrices for Deep Neural Networks》
No 22. 《Interdisciplinary Relationships Between Biological and Physical Sciences》
No 23. 《Interactive Image Generation Using Scene Graphs》
No 24. 《Multi-Person Pose Estimation with Enhanced Channel-wise and Spatial Information》
No 25. 《Evaluation of Machine Learning Classifiers for Zero-Day Intrusion Detection — An Analysis on CIC-AWS-2018 dataset》
No 26. 《Structural Equation Modeling using Computation Graphs》
No 27. 《Machine Learning at Microsoft with ML .NET》
No 28. 《AutoAssist: A Framework to Accelerate Training of Deep Neural Networks》
No 29. 《Learning Causality: Synthesis of Large-Scale Causal Networks from High-Dimensional Time Series Data》
No 30. 《Learning to Interpret Satellite Images in Global Scale Using Wikipedia》