User contributions for Sosadatr
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6 November 2017
- 23:0423:04, 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
- 22:5322:53, 6 November 2017 diff hist +2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 22:2022:20, 6 November 2017 diff hist +8 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks No edit summary
- 14:3014:30, 6 November 2017 diff hist +37 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →How to increase RF size?
- 14:2614:26, 6 November 2017 diff hist +226 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-uniform Kernels
- 14:2314:23, 6 November 2017 diff hist +335 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-uniform Kernels
- 14:1514:15, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 14:1414:14, 6 November 2017 diff hist +61 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 14:1214:12, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 14:1214:12, 6 November 2017 diff hist +280 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 14:0714:07, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Random Weights
- 14:0614:06, 6 November 2017 diff hist +978 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 13:3513:35, 6 November 2017 diff hist +24 User:Sosadatr No edit summary current
- 06:3006:30, 6 November 2017 diff hist +192 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 05:4905:49, 6 November 2017 diff hist +11 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-linear Activation Functions
- 05:4805:48, 6 November 2017 diff hist +329 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-linear Activation Functions
- 05:3305:33, 6 November 2017 diff hist −8 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Verifying Theoretical Results
- 05:3205:32, 6 November 2017 diff hist +304 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Verifying Theoretical Results
- 05:2405:24, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 05:2005:20, 6 November 2017 diff hist +6 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 05:1805:18, 6 November 2017 diff hist +1 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 05:1705:17, 6 November 2017 diff hist +394 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 04:5204:52, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Verifying Theoretical Results
- 04:5204:52, 6 November 2017 diff hist +2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →References
- 04:4504:45, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-Linear Activation Functions
- 04:4404:44, 6 November 2017 diff hist 0 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Non-Uniform Kernels
- 04:4104:41, 6 November 2017 diff hist +113 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks No edit summary
- 04:3104:31, 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
- 04:2804:28, 6 November 2017 diff hist +99 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Discussion
- 04:2204:22, 6 November 2017 diff hist +5 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Discussion
- 04:2104:21, 6 November 2017 diff hist +32 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Discussion
- 04:2004:20, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →How the ERF evolves during training
- 04:2004:20, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Critique
- 04:2004:20, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Summary & Conclusion
- 01:5901:59, 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
- 01:5701:57, 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
- 01:5601:56, 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
- 01:5501:55, 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
- 01:5201:52, 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
- 01:5101:51, 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
- 01:4001:40, 6 November 2017 diff hist −2 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 01:3901:39, 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
- 01:3401:34, 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
- 01:3301:33, 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
- 01:2301:23, 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
- 01:2101:21, 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
- 01:2101:21, 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
- 01:1801:18, 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
- 01:1701:17, 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
- 01:1601:16, 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