爱可可老师一周论文精选(2020.1.11)

No 1. 《End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models》
No 2. 《A General and Adaptive Robust Loss Function》
No 3. 《Quantum Adversarial Machine Learning》
No 4. 《DeepHuman: 3D Human Reconstruction From a Single Image》
No 5. 《Beyond BLEU:Training Neural Machine Translation with Semantic Similarity》
No 6. 《Computational model discovery with reinforcement learning》
No 7. 《Semi-Supervised Learning with Normalizing Flows》
No 8. 《Randomly Projected Additive Gaussian Processes for Regression》
No 9. 《Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning》
No 10. 《CondConv: Conditionally Parameterized Convolutions for Efficient Inference》
No 11. 《From Research to Production and Back: Ludicrously Fast Neural Machine Translation》
No 12. 《Sea-Thru: A Method for Removing Water From Underwater Images》
No 13. 《Comparing Fine-tuning and Rewinding in Neural Network Pruning》
No 14. 《Gradient L1 Regularization for Quantization Robustness》
No 15. 《InverseRenderNet: Learning Single Image Inverse Rendering》
No 16. 《TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising》
No 17. 《MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection》
No 18. 《Unsupervised pre-training for sequence to sequence speech recognition》
No 19. 《From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction》
No 20. 《Disentangling Factors of Variations Using Few Labels》
No 21. 《Spectral Metric for Dataset Complexity Assessment》
No 22. 《The Myth of Double-Blind Review Revisited: ACL vs. EMNLP》
No 23. 《A Gentle Introduction to Deep Learning for Graphs》
No 24. 《Deep Graph Similarity Learning: A Survey》
No 25. 《On Bonus Based Exploration Methods In The Arcade Learning Environment》
No 26. 《MLPerf Training Benchmark》
No 27. 《Improving Deep Neuroevolution via Deep Innovation Protection》
No 28. 《Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity》
No 29. 《MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning》
No 30. 《Interdisciplinary Relationships Between Biological and Physical Sciences》

发表评论