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

21. Batch Normalization Summary
22. Bayesian Network as a Decision Tool for Predicting ALS Disease
23. Being Bayesian about Categorical Probability
24. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
25. Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
26. Bsodjahi
27. CRITICAL ANALYSIS OF SELF-SUPERVISION
28. CapsuleNets
29. CatBoost: unbiased boosting with categorical features
30. Co-Teaching
31. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
32. Convolutional Neural Networks for Sentence Classification
33. Convolutional Sequence to Sequence Learning
34. Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
35. Countering Adversarial Images Using Input Transformations
36. Curiosity-driven Exploration by Self-supervised Prediction
37. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
38. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
39. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
40. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
41. DeepVO Towards end to end visual odometry with deep RNN
42. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
43. Deep Double Descent Where Bigger Models and More Data Hurt
44. Deep Exploration via Bootstrapped DQN
45. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
46. Deep Learning for Extreme Multi-label Text Classification
47. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
48. Deep Residual Learning for Image Recognition
49. Deep Residual Learning for Image Recognition Summary
50. Deep Transfer Learning with Joint Adaptation Networks
51. Dense Passage Retrieval for Open-Domain Question Answering
52. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
53. Describtion of Text Mining
54. Dialog-based Language Learning
55. Do Deep Neural Networks Suffer from Crowding
56. Do Vision Transformers See Like CNN
57. Don't Just Blame Over-parametrization
58. Don't Just Blame Over-parametrization Summary
59. Dynamic Routing Between Capsules
60. Dynamic Routing Between Capsules STAT946
61. Dynamic Routing Between Capsulesl
62. Efficient kNN Classification with Different Numbers of Nearest Neighbors
63. End-to-End Differentiable Adversarial Imitation Learning
64. End to end Active Object Tracking via Reinforcement Learning
65. Evaluating Machine Accuracy on ImageNet
66. Extreme Multi-label Text Classification
67. F18-STAT841-Proposal
68. F18-STAT946-Proposal
69. F21-STAT 441/841 CM 763-Proposal
70. F21-STAT 940-Proposal