%0 Journal Article %1 journals/corr/abs-1902-04942 %A Luther, Kyle %A Seung, H. Sebastian %D 2019 %J CoRR %K dblp %T Variance-Preserving Initialization Schemes Improve Deep Network Training: But Which Variance is Preserved? %U http://dblp.uni-trier.de/db/journals/corr/corr1902.html#abs-1902-04942 %V abs/1902.04942

@article{journals/corr/abs-1902-04942, added-at = {2019-05-21T00:00:00.000+0200}, author = {Luther, Kyle and Seung, H. Sebastian}, biburl = {https://www.bibsonomy.org/bibtex/271f250c2a687ae7934198d94d4fea25b/dblp}, ee = {http://arxiv.org/abs/1902.04942}, interhash = {941be1140f57d3a134daea0764c50350}, intrahash = {71f250c2a687ae7934198d94d4fea25b}, journal = {CoRR}, keywords = {dblp}, timestamp = {2019-05-22T11:45:05.000+0200}, title = {Variance-Preserving Initialization Schemes Improve Deep Network Training: But Which Variance is Preserved?}, url = {http://dblp.uni-trier.de/db/journals/corr/corr1902.html#abs-1902-04942}, volume = {abs/1902.04942}, year = 2019 }