Rita Lyu

CrabNet hyperparameters is a benchmarking with 20 continuous and 3 categorical inputs. To avoid the constraints error, the 20 continuous parameters are treated as discrete values. This resolves the error...

Hi @AVHopp I have rebased to `main`. Though, now I got the error at `simulate_scenarios`. For example, when I run the small example you construct at #454 , I receive...

Hi @AdrianSosic, coding convention and some minor changes are updated. Similarly, transfer learning with different initial data size need attention. Line [333](https://github.com/ritalyu17/baybe/blob/7a9becde64a7d0b09f91a274d2c7cb654389bc26/benchmarks/domains/CrabNet_AdvOpt.py#L333)-349 in CrabNet benchmark.

Hi @AdrianSosic, I have incorporated the changes and rebased to main similar to the other benchmarks. Though, when running transfer learning for CrabNet, I got the `baybe.exceptions.NothingToSimulateError`. The set up...

Thanks for following up on this. The code was ready for review in March, and I’ve been keeping it on hold as I understood priorities were elsewhere. Happy to pick...

The hardness benchmark is ready for review and some feedbacks. Currently, the bayesian optimization component and multi-task component are set to two `Benchmark`. Main reason for seperating them is because...

Thanks for the information. No rush.

Hi Adrian, thank you for following up. I am planning on wrapping this up by end of this week. On Tue, Feb 25, 2025 at 8:47 AM AdrianSosic ***@***.***> wrote:...

Hi @AdrianSosic, I have updated both benchmarks to match the coding convention with other scripts in the repository. There is one thing that I couldn't quite figure out with, benchmark...

Hi @AdrianSosic, thanks for the suggestions. This pull request is ready for review.