Alessandro Flati

Please pull latest version.

If you have a GPU which supports CUDA, ` torch.device('cuda' if torch.cuda.is_available() else 'cpu')` will return `'cuda'`. That said, if you didn't install pytorch with `+cu121` or similar, you'll get...

I'd like to highlight an example that vividly illustrates the potential advantage of employing a continuous learning approach, like the one we propose with symbolic activation functions in KANs, over...

Sorry to be pedantic, but more and more examples come to my mind, An illustrative example of the benefits offered by expanding the function space of activation functions in KANs,...

> This sounds a lot like the Closed Form Liquid Time Constant networks. https://github.com/raminmh/liquid_time_constant_networks https://github.com/raminmh/CfC > > I wonder what @raminmh thinks about it? Mmmh I only see similarity in...

I do agree with @Jim137. BTW, if you already set device in the calling function there's no need to do so. If you want it to be transparent, even if...

Please confront #123

Could you print `symbolic_formula[0][0]` and/or share the notebook please?

Ok, this adds valuable information for me. The point is that the network, altough "pruned", is still a forward connected graph - so even if you don't see the edges,...

Please give a look to #123