Hello, I have a question about the usage of this code and paper
(Visualizing the Loss Landscape of Neural Nets[https://arxiv.org/abs/1712.09913])
I've read the original paper and ran this code with my code.
I have a plan that I want to write some SCI paper and you know that those papers need the reasons.
The topic of my paper is proposing a new method of classification training method and it works with existing models like VGGs.
But the thing is... I have to find out why the model is generalized more welly with existing feature extractor models.
Actually, the result of your code shows more generalized welly.
(A little bit more wide minima in 2d-plotting(like Figure 6 in the paper) and more blueish color of filter-normalized surface plotting with a ratio of eigenvalues.)
So my question is below:
Can I use the result of the 2d-plotting result(like Figure 6 in the paper) and a ratio of hessian eigenvalue(like Figure 7) as the reason of my proposing training method makes more welly generalized weight parameters if each result shows more wide rounded circle and more bluish color?
Hello, I have a question about the usage of this code and paper (Visualizing the Loss Landscape of Neural Nets[https://arxiv.org/abs/1712.09913])
I've read the original paper and ran this code with my code. I have a plan that I want to write some SCI paper and you know that those papers need the reasons. The topic of my paper is proposing a new method of classification training method and it works with existing models like VGGs. But the thing is... I have to find out why the model is generalized more welly with existing feature extractor models. Actually, the result of your code shows more generalized welly. (A little bit more wide minima in 2d-plotting(like Figure 6 in the paper) and more blueish color of filter-normalized surface plotting with a ratio of eigenvalues.)
So my question is below: Can I use the result of the 2d-plotting result(like Figure 6 in the paper) and a ratio of hessian eigenvalue(like Figure 7) as the reason of my proposing training method makes more welly generalized weight parameters if each result shows more wide rounded circle and more bluish color?