Replace GPy with Gpytorch in TSEMO #94
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This PR switches TSEMO to use the Gaussian Process models from Botorch/GPytorch instead of GPy. As noted in #92, GPy has been causing problems during training. Switching to Botorch models resolved this. This is a refactor in that the external APIs are all remaining the same.
To confirm that there is no regression in performance, I reran the SnAr benchmark experiments with TSEMO and the performance was comparable to the paper (average terminal hypervolume of ~5600). The results are in
summit_tsemo_snar.xlsx.