Uncategorized pages

Showing below up to 50 results in range #61 to #110.

61. Dynamic Routing Between Capsules STAT946
62. Dynamic Routing Between Capsulesl
63. Efficient kNN Classification with Different Numbers of Nearest Neighbors
64. End-to-End Differentiable Adversarial Imitation Learning
65. End to end Active Object Tracking via Reinforcement Learning
66. Evaluating Machine Accuracy on ImageNet
67. Extreme Multi-label Text Classification
68. F18-STAT841-Proposal
69. F18-STAT946-Proposal
70. F21-STAT 441/841 CM 763-Proposal
71. F21-STAT 940-Proposal
72. Fairness Without Demographics in Repeated Loss Minimization
73. FeUdal Networks for Hierarchical Reinforcement Learning
74. Fix your classifier: the marginal value of training the last weight layer
75. From Variational to Deterministic Autoencoders
76. Functional regularisation for continual learning with gaussian processes
77. Generating Image Descriptions
78. Going Deeper with Convolutions
79. GradientLess Descent
80. Gradient Episodic Memory for Continual Learning
81. Graph Structure of Neural Networks
82. Hash Embeddings for Efficient Word Representations
83. Hierarchical Question-Image Co-Attention for Visual Question Answering
84. Hierarchical Representations for Efficient Architecture Search
85. IPBoost
86. Imagination-Augmented Agents for Deep Reinforcement Learning
87. Imagination Augmented Agents for Deep Reinforcement Learning
88. Improving neural networks by preventing co-adaption of feature detectors
89. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
90. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
91. Influenza Forecasting Framework based on Gaussian Processes
92. Influenza Forecasting Framework based on Gaussian processes Summary
93. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
94. Learning Combinatorial Optimzation
95. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
96. Learning What and Where to Draw
97. Learning the Number of Neurons in Deep Networks
98. Learning to Navigate in Cities Without a Map
99. Learning to Teach
100. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
101. Loss Function Search for Face Recognition
102. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
103. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
104. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
105. Mask RCNN
106. Memory-Based Parameter Adaptation
107. Meta-Learning-For-Domain Generalization
108. Meta-Learning For Domain Generalization
109. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
110. ModelFramework.jpg