<p>The confusion arise from the naming convention, the difference is naming with first name or surname. Basically, the initialization method proposed in <a href="https://arxiv.org/abs/1502.01852" rel="noreferrer">this paper</a> co-authored by Kaiming He. The framework implementations differ, however;</p>
<p>Tensorflow via Keras backend uses the name <code>He</code> initilization. Torch uses <code>Kaiming</code> initilization as the method names.</p>
<p>In fact, the same applies also for Glorot/Xavier initialization. See <a href="http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf" rel="noreferrer">the paper</a> co-authored by Xavier Glorot.</p>
<p>Here, Tensorflow via Keras uses the surname <code>Glorot</code> whereas Torch uses the first name <code>Xavier</code>.</p>
Kaiming initialization for keras
<p>My model layers are using <strong>relu activation function</strong>. I am <strong>using he_uniform for the kernel initializer</strong>, but i saw <em><strong>kaiming initialization giving better result than he_uniform</strong></em>. I m using keras, and keras has no kaiming initializer, how can I implement it?</p>