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Showing below up to 50 results in range #21 to #70.

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  1. Batch Normalization
  2. Batch Normalization Summary
  3. Bayesian Network as a Decision Tool for Predicting ALS Disease
  4. Being Bayesian about Categorical Probability
  5. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
  6. Bsodjahi
  7. CRITICAL ANALYSIS OF SELF-SUPERVISION
  8. CapsuleNets
  9. CatBoost: unbiased boosting with categorical features
  10. Co-Teaching
  11. Conditional Image Synthesis with Auxiliary Classifier GANs
  12. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
  13. Convolutional Neural Networks for Sentence Classification
  14. Convolutional Sequence to Sequence Learning
  15. Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
  16. Countering Adversarial Images Using Input Transformations
  17. Curiosity-driven Exploration by Self-supervised Prediction
  18. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
  19. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
  20. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
  21. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
  22. DeepVO Towards end to end visual odometry with deep RNN
  23. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
  24. Deep Double Descent Where Bigger Models and More Data Hurt
  25. Deep Exploration via Bootstrapped DQN
  26. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
  27. Deep Learning for Extreme Multi-label Text Classification
  28. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
  29. Deep Residual Learning for Image Recognition
  30. Deep Residual Learning for Image Recognition Summary
  31. Deep Transfer Learning with Joint Adaptation Networks
  32. Dense Passage Retrieval for Open-Domain Question Answering
  33. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
  34. Describtion of Text Mining
  35. Dialog-based Language Learning
  36. Do Deep Neural Networks Suffer from Crowding
  37. Do Vision Transformers See Like CNN
  38. Don't Just Blame Over-parametrization
  39. Don't Just Blame Over-parametrization Summary
  40. Dynamic Routing Between Capsules
  41. Dynamic Routing Between Capsules STAT946
  42. Dynamic Routing Between Capsulesl
  43. Efficient kNN Classification with Different Numbers of Nearest Neighbors
  44. End-to-End Differentiable Adversarial Imitation Learning
  45. End to end Active Object Tracking via Reinforcement Learning
  46. Evaluating Machine Accuracy on ImageNet
  47. Extreme Multi-label Text Classification
  48. F18-STAT841-Proposal
  49. F18-STAT946-Proposal
  50. F21-STAT 441/841 CM 763-Proposal

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