User contributions for Nkadiyar
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28 November 2017
- 13:0813:08, 28 November 2017 diff hist 0 STAT946F17/ Automated Curriculum Learning for Neural Networks No edit summary
- 13:0713:07, 28 November 2017 diff hist −2 STAT946F17/Decoding with Value Networks for Neural Machine Translation No edit summary
23 November 2017
- 13:1313:13, 23 November 2017 diff hist +1 STAT946F17/Conditional Image Generation with PixelCNN Decoders No edit summary
- 13:1113:11, 23 November 2017 diff hist +3 Hierarchical Question-Image Co-Attention for Visual Question Answering No edit summary
- 13:0813:08, 23 November 2017 diff hist 0 Hierarchical Question-Image Co-Attention for Visual Question Answering No edit summary
- 13:0713:07, 23 November 2017 diff hist +1 Conditional Image Synthesis with Auxiliary Classifier GANs No edit summary
- 13:0513:05, 23 November 2017 diff hist −1 Conditional Image Synthesis with Auxiliary Classifier GANs No edit summary
- 13:0413:04, 23 November 2017 diff hist −1 Conditional Image Synthesis with Auxiliary Classifier GANs No edit summary
22 November 2017
- 14:3014:30, 22 November 2017 diff hist +86 Unsupervised Domain Adaptation with Residual Transfer Networks →References
- 14:0514:05, 22 November 2017 diff hist +621 Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks →Introduction & Background
- 13:5113:51, 22 November 2017 diff hist 0 Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks →Problem set-up
- 13:4813:48, 22 November 2017 diff hist +223 Deep Exploration via Bootstrapped DQN →Q Learning and Deep Q Networks [[#References|[5]]]
21 November 2017
- 12:3012:30, 21 November 2017 diff hist +6 Unsupervised Domain Adaptation with Residual Transfer Networks No edit summary
- 12:2712:27, 21 November 2017 diff hist +5 Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks No edit summary
- 12:2312:23, 21 November 2017 diff hist +2 Deep Exploration via Bootstrapped DQN No edit summary
20 November 2017
- 23:5923:59, 20 November 2017 diff hist +100 Modular Multitask Reinforcement Learning with Policy Sketches →Introduction & Background
19 November 2017
- 14:2014:20, 19 November 2017 diff hist +64 Universal Style Transfer via Feature Transforms →Content/Style Balance
- 14:1414:14, 19 November 2017 diff hist +67 Universal Style Transfer via Feature Transforms →Introduction
- 14:1214:12, 19 November 2017 diff hist +100 Universal Style Transfer via Feature Transforms →Introduction
- 13:3613:36, 19 November 2017 diff hist +49 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →References
- 13:3513:35, 19 November 2017 diff hist +308 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →Introduction
- 13:2713:27, 19 November 2017 diff hist −4 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →Adaptive Network Input
- 13:2613:26, 19 November 2017 diff hist +148 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition No edit summary
- 13:2313:23, 19 November 2017 diff hist +54 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →References
- 13:2213:22, 19 November 2017 diff hist +3 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →Introduction
- 13:2213:22, 19 November 2017 diff hist +94 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →Introduction
- 13:1913:19, 19 November 2017 diff hist +28 N File:ActionRecognition1.jpg Action Recognition in Videos current
- 13:1513:15, 19 November 2017 diff hist +91 Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition →Introduction
15 November 2017
- 13:2213:22, 15 November 2017 diff hist +13 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part I: 2-Component Shared Embedding
- 13:2113:21, 15 November 2017 diff hist +98 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →LightRNN Structure
- 13:1513:15, 15 November 2017 diff hist +95 "Why Should I Trust You?": Explaining the Predictions of Any Classifier →Fidelity-Interpretability Trade-Off
- 09:0009:00, 15 November 2017 diff hist +65 STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback →Related Works
- 08:5708:57, 15 November 2017 diff hist +41 STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback →Introduction
13 November 2017
- 18:4618:46, 13 November 2017 diff hist −1 STAT946F17/ Coupled GAN →Introduction
- 18:3418:34, 13 November 2017 diff hist +241 Imagination-Augmented Agents for Deep Reinforcement Learning →Introduction
8 November 2017
- 20:2020:20, 8 November 2017 diff hist +1 Learning the Number of Neurons in Deep Networks →Model Training and Model Selection
- 20:1120:11, 8 November 2017 diff hist +55 Learning the Number of Neurons in Deep Networks →Introduction
- 20:0820:08, 8 November 2017 diff hist +9 Learning the Number of Neurons in Deep Networks →Introduction
- 19:5719:57, 8 November 2017 diff hist +9 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Cognitive Biases
- 19:5619:56, 8 November 2017 diff hist +105 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Cognitive Biases
- 19:5319:53, 8 November 2017 diff hist +278 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Cognitive Biases
- 19:4319:43, 8 November 2017 diff hist +2 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Matching Networks
- 19:4119:41, 8 November 2017 diff hist +1 Dialog-based Language Learning →Training strategies
- 19:4019:40, 8 November 2017 diff hist +1 Dialog-based Language Learning →Learning models
- 19:3019:30, 8 November 2017 diff hist −4 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Introduction
- 19:0419:04, 8 November 2017 diff hist +20 FeUdal Networks for Hierarchical Reinforcement Learning →Learning: - The reward from the environment is different from the intrinsic reward followed by the Worker. Be specific to avoid confusion
- 18:3318:33, 8 November 2017 diff hist −2 FeUdal Networks for Hierarchical Reinforcement Learning →Introduction