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  1. "Why Should I Trust You?": Explaining the Predictions of Any Classifier
  2. ALBERT
  3. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
  4. A Bayesian Perspective on Generalization and Stochastic Gradient Descent
  5. A Knowledge-Grounded Neural Conversation Model
  6. A Neural Representation of Sketch Drawings
  7. A universal SNP and small-indel variant caller using deep neural networks
  8. Adacompress: Adaptive compression for online computer vision services
  9. Adversarial Fisher Vectors for Unsupervised Representation Learning
  10. Annotating Object Instances with a Polygon RNN
  11. Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
  12. Augmix: New Data Augmentation method to increase the robustness of the algorithm
  13. Bag of Tricks for Efficient Text Classification
  14. Batch Normalization
  15. Batch Normalization Summary
  16. Being Bayesian about Categorical Probability
  17. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
  18. Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
  19. CRITICAL ANALYSIS OF SELF-SUPERVISION
  20. CapsuleNets
  21. Co-Teaching
  22. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
  23. Convolutional Neural Networks for Sentence Classification
  24. Convolutional Sequence to Sequence Learning
  25. Countering Adversarial Images Using Input Transformations
  26. Curiosity-driven Exploration by Self-supervised Prediction
  27. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
  28. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
  29. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
  30. DeepVO Towards end to end visual odometry with deep RNN
  31. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
  32. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
  33. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
  34. Deep Residual Learning for Image Recognition
  35. Deep Transfer Learning with Joint Adaptation Networks
  36. Dense Passage Retrieval for Open-Domain Question Answering
  37. Describtion of Text Mining
  38. Do Deep Neural Networks Suffer from Crowding
  39. Dynamic Routing Between Capsules
  40. Dynamic Routing Between Capsules STAT946
  41. Dynamic Routing Between Capsulesl
  42. End-to-End Differentiable Adversarial Imitation Learning
  43. End to end Active Object Tracking via Reinforcement Learning
  44. Evaluating Machine Accuracy on ImageNet
  45. Extreme Multi-label Text Classification
  46. Fairness Without Demographics in Repeated Loss Minimization
  47. FeUdal Networks for Hierarchical Reinforcement Learning
  48. Fix your classifier: the marginal value of training the last weight layer
  49. From Variational to Deterministic Autoencoders
  50. Functional regularisation for continual learning with gaussian processes

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