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Showing below up to 100 results in range #21 to #120.

21. Batch Normalization
22. Batch Normalization Summary
23. Bayesian Network as a Decision Tool for Predicting ALS Disease
24. Being Bayesian about Categorical Probability
25. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
26. Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
27. Bsodjahi
28. CRITICAL ANALYSIS OF SELF-SUPERVISION
29. CapsuleNets
30. CatBoost: unbiased boosting with categorical features
31. Co-Teaching
32. Conditional Image Synthesis with Auxiliary Classifier GANs
33. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
34. Convolutional Neural Networks for Sentence Classification
35. Convolutional Sequence to Sequence Learning
36. Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
37. Countering Adversarial Images Using Input Transformations
38. Curiosity-driven Exploration by Self-supervised Prediction
39. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
40. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
41. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
42. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
43. DeepVO Towards end to end visual odometry with deep RNN
44. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
45. Deep Double Descent Where Bigger Models and More Data Hurt
46. Deep Exploration via Bootstrapped DQN
47. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
48. Deep Learning for Extreme Multi-label Text Classification
49. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
50. Deep Residual Learning for Image Recognition
51. Deep Residual Learning for Image Recognition Summary
52. Deep Transfer Learning with Joint Adaptation Networks
53. Dense Passage Retrieval for Open-Domain Question Answering
54. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
55. Describtion of Text Mining
56. Dialog-based Language Learning
57. Do Deep Neural Networks Suffer from Crowding
58. Do Vision Transformers See Like CNN
59. Don't Just Blame Over-parametrization
60. Don't Just Blame Over-parametrization Summary
61. Dynamic Routing Between Capsules
62. Dynamic Routing Between Capsules STAT946
63. Dynamic Routing Between Capsulesl
64. Efficient kNN Classification with Different Numbers of Nearest Neighbors
65. End-to-End Differentiable Adversarial Imitation Learning
66. End to end Active Object Tracking via Reinforcement Learning
67. Evaluating Machine Accuracy on ImageNet
68. Extreme Multi-label Text Classification
69. F18-STAT841-Proposal
70. F18-STAT946-Proposal
71. F21-STAT 441/841 CM 763-Proposal
72. F21-STAT 940-Proposal
73. Fairness Without Demographics in Repeated Loss Minimization
74. FeUdal Networks for Hierarchical Reinforcement Learning
75. Fix your classifier: the marginal value of training the last weight layer
76. From Variational to Deterministic Autoencoders
77. Functional regularisation for continual learning with gaussian processes
78. Generating Image Descriptions
79. Going Deeper with Convolutions
80. GradientLess Descent
81. Gradient Episodic Memory for Continual Learning
82. Graph Structure of Neural Networks
83. Hash Embeddings for Efficient Word Representations
84. Hierarchical Question-Image Co-Attention for Visual Question Answering
85. Hierarchical Representations for Efficient Architecture Search
86. IPBoost
87. Imagination-Augmented Agents for Deep Reinforcement Learning
88. Imagination Augmented Agents for Deep Reinforcement Learning
89. Improving neural networks by preventing co-adaption of feature detectors
90. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
91. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
92. Influenza Forecasting Framework based on Gaussian Processes
93. Influenza Forecasting Framework based on Gaussian processes Summary
94. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
95. Learning Combinatorial Optimzation
96. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
97. Learning What and Where to Draw
98. Learning the Number of Neurons in Deep Networks
99. Learning to Navigate in Cities Without a Map
100. Learning to Teach
101. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
102. Loss Function Search for Face Recognition
103. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
104. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
105. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
106. Mask RCNN
107. Memory-Based Parameter Adaptation
108. Meta-Learning-For-Domain Generalization
109. Meta-Learning For Domain Generalization
110. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
111. ModelFramework.jpg
112. Model Agnostic Learning of Semantic Features
113. Modular Multitask Reinforcement Learning with Policy Sketches
114. Multi-scale Dense Networks for Resource Efficient Image Classification
115. Music Recommender System Based using CRNN
116. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
117. Neural ODEs
118. Neural Speed Reading via Skim-RNN
119. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
120. On The Convergence Of ADAM And Beyond