Paul Shen
Paul Shen
Thank you I appreciate it.
@Dsantra92 You can try our [EquivariantOperators.jl](https://aced-differentiate.github.io/EquivariantOperators.jl/) [Tutorials on colab](https://colab.research.google.com/drive/17JZEdK6aALxvn0JPBJEHGeK2nO1hPnhQ#scrollTo=4utBHhoeHzRY) [Paper Preprint](http://arxiv.org/abs/2108.09541)
Thanks will do
Thanks @Dsantra92 I believe @CarloLucibello dug up the subfolder containing output from the script in the same format as MNIST data
Thank you both. I appreciate it.
Doesn't `sol(t).x` work already?
Thanks I found updated implementation in Optim.jl https://github.com/JuliaNLSolvers/Optim.jl/blob/master/src/multivariate/solvers/first_order/l_bfgs.jl Doesn't look too hard to port to Optimisers.jl? We can omit linesearch. Flux assumes each function evaluation is expensive.
Update: problem arises on Google Colab and not in AWS VMs. Problem persists with julia11.4 cuda.jl5.7 . But I need this to work on Colab! Happy to pay couple hours...
Thanks I did PR for obj - numbertype wasn't passed to objread