User contributions for Ashishgaurav
A user with 78 edits. Account created on 25 September 2017.
14 November 2017
- 04:2804:28, 14 November 2017 diff hist +2 STAT946F17/ Coupled GAN →Coupled GAN (CoGAN) Framework and Learning
- 04:2704:27, 14 November 2017 diff hist +3 STAT946F17/ Coupled GAN →Coupled GAN (CoGAN) Framework and Learning
- 04:2604:26, 14 November 2017 diff hist +135 STAT946F17/ Coupled GAN →References and Supplementary Resources
- 04:2004:20, 14 November 2017 diff hist 0 m STAT946F17/ Coupled GAN →Coupled GAN (CoGAN) Framework and Learning
9 November 2017
- 12:3112:31, 9 November 2017 diff hist +16 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Modeling human word learning
- 12:3112:31, 9 November 2017 diff hist +636 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →References
- 12:2412:24, 9 November 2017 diff hist +50 STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study →Data Sets Used
- 12:1912:19, 9 November 2017 diff hist +9 FeUdal Networks for Hierarchical Reinforcement Learning →Conclusion
- 12:1112:11, 9 November 2017 diff hist +139 FeUdal Networks for Hierarchical Reinforcement Learning →Introduction
- 12:0612:06, 9 November 2017 diff hist +132 Learning the Number of Neurons in Deep Networks →Model Training and Model Selection
- 11:3711:37, 9 November 2017 diff hist +11 Learning the Number of Neurons in Deep Networks →Conclusion
- 11:3711:37, 9 November 2017 diff hist 0 Learning the Number of Neurons in Deep Networks →Analysis on Testing
- 11:3411:34, 9 November 2017 diff hist +1 Learning the Number of Neurons in Deep Networks →Introduction
- 11:3411:34, 9 November 2017 diff hist +20 Learning the Number of Neurons in Deep Networks No edit summary
7 November 2017
- 13:3113:31, 7 November 2017 diff hist +18 Convolutional Sequence to Sequence Learning →Results
- 13:2713:27, 7 November 2017 diff hist +80 Convolutional Sequence to Sequence Learning →Background
- 13:1213:12, 7 November 2017 diff hist +346 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-uniform Kernels
- 11:3311:33, 7 November 2017 diff hist +11 m meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting →Proposed Approach
- 11:2111:21, 7 November 2017 diff hist +50 m meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting →Introduction
2 November 2017
- 03:5803:58, 2 November 2017 diff hist +113 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary add eqn 10 that gives the value of y_i in eqn 9