User contributions for Sosadatr
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6 November 2017
- 22:0422:04, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 21:5321:53, 6 November 2017 diff hist +2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 21:2021:20, 6 November 2017 diff hist +8 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks No edit summary
- 13:3013:30, 6 November 2017 diff hist +37 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →How to increase RF size?
- 13:2613:26, 6 November 2017 diff hist +226 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-uniform Kernels
- 13:2313:23, 6 November 2017 diff hist +335 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-uniform Kernels
- 13:1513:15, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 13:1413:14, 6 November 2017 diff hist +61 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 13:1213:12, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 13:1213:12, 6 November 2017 diff hist +280 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 13:0713:07, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 13:0613:06, 6 November 2017 diff hist +978 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 12:3512:35, 6 November 2017 diff hist +24 User:Sosadatr No edit summary current
- 05:3005:30, 6 November 2017 diff hist +192 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 04:4904:49, 6 November 2017 diff hist +11 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-linear Activation Functions
- 04:4804:48, 6 November 2017 diff hist +329 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-linear Activation Functions
- 04:3304:33, 6 November 2017 diff hist −8 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Verifying Theoretical Results
- 04:3204:32, 6 November 2017 diff hist +304 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Verifying Theoretical Results
- 04:2404:24, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 04:2004:20, 6 November 2017 diff hist +6 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 04:1804:18, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 04:1704:17, 6 November 2017 diff hist +394 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 03:5203:52, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Verifying Theoretical Results
- 03:5203:52, 6 November 2017 diff hist +2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →References
- 03:4503:45, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-Linear Activation Functions
- 03:4403:44, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-Uniform Kernels
- 03:4103:41, 6 November 2017 diff hist +113 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks No edit summary
- 03:3103:31, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 03:2803:28, 6 November 2017 diff hist +99 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Discussion
- 03:2203:22, 6 November 2017 diff hist +5 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Discussion
- 03:2103:21, 6 November 2017 diff hist +32 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Discussion
- 03:2003:20, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →How the ERF evolves during training
- 03:2003:20, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 03:2003:20, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Summary & Conclusion
- 00:5900:59, 6 November 2017 diff hist +166 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:5700:57, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:5600:56, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:5500:55, 6 November 2017 diff hist +40 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:5200:52, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:5100:51, 6 November 2017 diff hist +157 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:4000:40, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 00:3900:39, 6 November 2017 diff hist +224 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:3400:34, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:3300:33, 6 November 2017 diff hist +308 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:2300:23, 6 November 2017 diff hist +2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:2100:21, 6 November 2017 diff hist −9 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:2100:21, 6 November 2017 diff hist +50 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:1800:18, 6 November 2017 diff hist +7 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:1700:17, 6 November 2017 diff hist −12 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 00:1600:16, 6 November 2017 diff hist +20 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1