No 1. 《Enriching BERT with Knowledge Graph Embeddings for Document Classification》
    No 2. 《Understanding LSTM — a tutorial into Long Short-Term Memory Recurrent Neural Networks》
    No 3. 《Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning》
    No 4. 《Reinforcement Learning for Portfolio Management》
    No 5. 《Chargrid-OCR: End-to-end trainable Optical Character Recognition through Semantic Segmentation and Object Detection》
    No 6. 《Data Augmentation Revisited: Rethinking the Distribution Gap between Clean and Augmented Data》
    No 7. 《PyDEns: a Python Framework for Solving Differential Equations with Neural Networks》
    No 8. 《Flight Controller Synthesis Via Deep Reinforcement Learning》
    No 9. 《Unsupervised Learning for Real-World Super-Resolution》
    No 10. 《Domain Aggregation Networks for Multi-Source Domain Adaptation》
    No 11. 《Adversarial Attacks and Defenses in Images, Graphs and Text: A Review》
    No 12. 《InterpretML: A Unified Framework for Machine Learning Interpretability》
    No 13. 《Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models》
    No 14. 《Zero-Shot Action Recognition in Videos: A Survey》
    No 15. 《Synthetic Data for Deep Learning》
    No 16. 《On Understanding Knowledge Graph Representation》
    No 17. 《Attention Interpretability Across NLP Tasks》
    No 18. 《Adaptive Scheduling for Multi-Task Learning》
    No 19. 《Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making》
    No 20. 《Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis》
    No 21. 《A Full-Image Full-Resolution End-to-End-Trainable CNN Framework for Image Forgery Detection》
    No 22. 《Quantum Graph Neural Networks》
    No 23. 《Making the Invisible Visible: Action Recognition Through Walls and Occlusions》
    No 24. 《Rapid Bayesian inference for expensive stochastic models》
    No 25. 《Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML》
    No 26. 《Human Synthesis and Scene Compositing》
    No 27. 《Causal inference and machine learning approaches for evaluation of the health impacts of large-scale air quality regulations》
    No 28. 《Feedback Learning for Improving the Robustness of Neural Networks》
    No 29. 《Variational Conditional GAN for Fine-grained Controllable Image Generation》
    No 30. 《Counterfactual Cross-Validation: Effective Causal Model Selection from Observational Data》