18 Commits

Author	SHA1	Message	Date
Mattéo Delabre	d8a140d793	Simplify arguments for ConstellationNet	2019-12-18 10:26:35 -05:00
Mattéo Delabre	a7e9dd2230	Save whole model to avoid definition duplicate	2019-12-18 10:17:59 -05:00
Mattéo Delabre	0769a61fcf	Use best parameters as found by experimentation	2019-12-18 09:41:50 -05:00
Mattéo Delabre	e8e4dcec83	Set learning rate to 10^-3	2019-12-16 10:31:29 -05:00
Mattéo Delabre	af59421dc0	Fix variable naming clash	2019-12-16 10:31:16 -05:00
Mattéo Delabre	fb2518b321	Show final loss after training	2019-12-16 10:20:01 -05:00
Mattéo Delabre	1d39184036	Use euclidean distance for stop criterion	2019-12-16 09:55:06 -05:00
Mattéo Delabre	2c4786bdba	Remove reconstruction examples after training	2019-12-16 09:17:15 -05:00
Mattéo Delabre	8fa6b46ca8	Change training strategy to adaptive learning rate	2019-12-16 02:30:33 -05:00
Mattéo Delabre	3f2c6d18a3	Manually seed training for reproducibility	2019-12-16 01:50:03 -05:00
Mattéo Delabre	3638749998	Share plotting code between plot.py and train.py	2019-12-15 20:05:20 -05:00
Mattéo Delabre	59d7adf6bd	Add convergence criterion plot during train	2019-12-15 19:42:50 -05:00
Mattéo Delabre	989a51b72e	Increase batch size halfway through training	2019-12-15 09:42:48 -05:00
Mattéo Delabre	6ea0e653c1	Balance training examples	2019-12-15 00:59:10 -05:00
Mattéo Delabre	3b40e27070	Add Gaussian channel model	2019-12-14 23:04:35 -05:00
Mattéo Delabre	a01d83f339	Improve plot	2019-12-13 17:10:40 -05:00
Mattéo Delabre	49e63775dd	Save trained models and plot encoding	2019-12-13 15:17:57 -05:00
Mattéo Delabre	2af8354a07	Add initial implementation	2019-12-13 12:11:09 -05:00