text:   Initialization",7,"['1/4 A Signal Propagation Perspective for Pruning Neural Networks at Initialization: our new work on pruning neural networks at initialization is available now.\npaper: <LINK>\nwith @tha_ajanthan, Stephen Gould, Philip Torr.', '2/4 In SNIP (ICLR19), we showed that pruning can be done on a randomly initialized network without pretraining: ""pruning at initialization"". However, it\'s unclear exactly why pruning untrained networks is effective, how it should be understood, whether it can be extended further.', '3/4 This work provides a signal propagation perspective based on dynamical isometry and mean field theory to pruning at initialization. We improve performance by orthogonal initialization, present unsupervised pruning, and bring forth the notion of neural architecture sculpting.', '4/4 We are really excited about what this work could possibly bring us even more, so please stay tuned for our future endeavours!', '@_onionesque Thanks :))) Yeah I realized he had SNIPER paper a little while after I submitted SNIP; and of course I had chat with him about it :)', '@_onionesque Maybe I should name my future work SNIPER, aiming at the lottery ticket lol', '@_onionesque preempted here thanks to your help lol']",19,06,1199