LHCb Web>LHCbPPTS>PPTSConferencePlots (2016-04-08, PaulSeyfert)

Plots for Conference about Miscellaneous topics of PPTS

deep neural networks with domain adaptation

deep neural networks with domain adaptation

Discussed at the PPTS meeting on 4th April 2016, contribution

Plot	Description
.C .png .pdf	A proof of principle that caffe trained deep neural networks do the job of signal/background separation, in the ballpark of what we're used to from TMVA. This shall demonstrate that the caffe test setup works in principle and we can assume trainings have converged and we can go on to the next step
.C .png .pdf	A by-eye comparison of networks with and without domain adaptation. The signal to background is hardly distinguishable, the network without domain adaptation is even a bit better.

-- SilviaBorghi - 2016-04-07

Attachments

Topic attachments
I	Attachment	History	Action	Size	Date	Who	Comment
c	adding_grl_to_network.C	r1	manage	48.8 K	2016-04-08 - 10:34	PaulSeyfert	plots for deep learning with domain adaptation
pdf	adding_grl_to_network.pdf	r1	manage	36.9 K	2016-04-08 - 10:34	PaulSeyfert	plots for deep learning with domain adaptation
png	adding_grl_to_network.png	r1	manage	18.2 K	2016-04-08 - 10:34	PaulSeyfert	plots for deep learning with domain adaptation
c	caffe_vs_tmva.C	r1	manage	49.0 K	2016-04-08 - 10:34	PaulSeyfert	plots for deep learning with domain adaptation
pdf	caffe_vs_tmva.pdf	r1	manage	36.8 K	2016-04-08 - 10:34	PaulSeyfert	plots for deep learning with domain adaptation
png	caffe_vs_tmva.png	r1	manage	16.8 K	2016-04-08 - 10:34	PaulSeyfert	plots for deep learning with domain adaptation

Topic revision: r2 - 2016-04-08 - PaulSeyfert

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