User contributions for Sosadatr
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6 November 2017
- 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
- 01:1501:15, 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
- 01:1401:14, 6 November 2017 diff hist +8 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 01:1301:13, 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
- 01:1201:12, 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
- 01:1101:11, 6 November 2017 diff hist +22 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 01:0801:08, 6 November 2017 diff hist +6 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results
- 01:0701:07, 6 November 2017 diff hist −30 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 01:0701:07, 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
- 01:0601:06, 6 November 2017 diff hist +4 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Simplest case: Stack of convolutional layers of weights equal to 1
- 01:0501:05, 6 November 2017 diff hist +6 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Theoretical Results