User contributions for SophiaH
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1 November 2017
- 14:4014:40, 1 November 2017 diff hist +117 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →LightRNN Example
- 14:3814:38, 1 November 2017 diff hist 0 N File:Table3YH.PNG No edit summary current
- 14:3614:36, 1 November 2017 diff hist 0 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part III: Bootstrap for Word Allocation
- 13:1913:19, 1 November 2017 diff hist +1 Convolutional Sequence to Sequence Learning →Position Embeddings
- 12:2312:23, 1 November 2017 diff hist +200 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →References
- 12:2212:22, 1 November 2017 diff hist +614 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Why is RF important?
- 11:5811:58, 1 November 2017 diff hist +563 meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting →Related Work
- 11:4511:45, 1 November 2017 diff hist −3 meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting →Introduction
29 October 2017
- 18:2718:27, 29 October 2017 diff hist −6 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Natural Language Processing (NLP) Using Recurrent Neural Network (RNN)
28 October 2017
- 11:3611:36, 28 October 2017 diff hist +561 Learning the Number of Neurons in Deep Networks →Model Training and Model Selection
- 11:2211:22, 28 October 2017 diff hist +2 Learning the Number of Neurons in Deep Networks →Model Training and Model Selection
- 11:1611:16, 28 October 2017 diff hist +15 Learning the Number of Neurons in Deep Networks →Conclusion
- 11:1311:13, 28 October 2017 diff hist +12 Learning the Number of Neurons in Deep Networks →Introduction
- 11:0511:05, 28 October 2017 diff hist +5 STAT946F17/ Learning Important Features Through Propagating Activation Differences →Numerical results
- 11:0211:02, 28 October 2017 diff hist +8 STAT946F17/ Learning Important Features Through Propagating Activation Differences →Introduction
- 11:0111:01, 28 October 2017 diff hist +2 STAT946F17/ Learning Important Features Through Propagating Activation Differences →Introduction
- 10:5810:58, 28 October 2017 diff hist +2 STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN →Evaluation current
- 10:5410:54, 28 October 2017 diff hist +9 STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN →3D-VAE-GANs
- 10:4510:45, 28 October 2017 diff hist +681 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Lasso Regression and Model Selection:
- 10:2710:27, 28 October 2017 diff hist +328 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Ridge Regression and Overfitting: